Evidence map›Paper›PMID 35813398›Full record

ArticlePreventive medicine reports2022

Delayed medical care and underlying health in the United States during the COVID-19 pandemic: A cross-sectional study.

Autumn H Gertz, Catherine C Pollack, Marinanicole D Schultheiss, John S Brownstein

Abstract read
In one paragraph

Article in Preventive medicine reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
56citing papers in PubMed, 3 pooled it
–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

56 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
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  3. Facial Nerve Palsy Amid the SARS-CoV-2 Pandemic: A Pooled Analysis.Journal of otolaryngology - head & neck surgery = Le Journal d'oto-rhino-laryngologie et de chirurgie cervico-faciale
    Pooled it
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  13. Patient Healthcare Seeking If There Were No Limits.Journal of the American Board of Family Medicine : JABFM · 2025
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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

4 authors.

Autumn H GertzComputational Epidemiology Lab, Boston Children's Hospital, Boston, MA, USA.
Catherine C PollackComputational Epidemiology Lab, Boston Children's Hospital, Boston, MA, USA.
Marinanicole D SchultheissComputational Epidemiology Lab, Boston Children's Hospital, Boston, MA, USA.
John S BrownsteinComputational Epidemiology Lab, Boston Children's Hospital, Boston, MA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study assesses the association between underlying health conditions and delaying medical care during the COVID-19 pandemic. An online cross-sectional survey administered by OutbreaksNearMe.org on Momentive.ai collected self-reported data from April 27 to June 2, 2020 and May 10 to June 13, 2021. We used weighted multivariable logistic regressions to assess the association between delaying care and self-reported health status, adjusting for demographics. Of 312,661 total responses (99.6% completion rate), 17.1% reported delayed medical care. Compared to good health, those with poor health were more likely to delay care (AOR = 2.62, 95% CI [2.47, 2.78]). Individuals with any underlying condition (AOR = 1.62, 95% CI [1.58, 1.65]) and each of the conditions were more likely to delay care. Differences in delaying care were observed across region, year, and demographics. Our finding is that those at higher risk of severe COVID-19 were more likely to delay medical care in 2020 and 2021, which could exacerbate existing health conditions and existing disparities.

Indexed as

COVID-19Delayed medical careHealth outcomesUnderlying health conditions

Identifiers

PMID35813398
PMCPMC9254505

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.