Evidence map›Paper›PMID 35503754›Full record

ArticlePloS one2022

Cognitive factors influenced physical distancing adherence during the COVID-19 pandemic in a population-specific way.

Gillian A M Tarr, Keeley J Morris, Alyson B Harding, Samuel Jacobs, M Kumi Smith, Timothy R Church, Jesse D Berman, Austin Rau, Sato Ashida, Marizen R Ramirez

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.0field-weighted citation impact, top 26% 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

4 citing papers in PubMed, 6 citations in OpenAlex.

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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

10 authors at 2 institutions in 1 country.

Gillian A M TarrDivision of Environmental Health Sciences, School of Public Health, University of Minnesota, Minneapolis, MN, United States of America.ORCID 0000-0001-7372-1034
Keeley J MorrisDivision of Epidemiology & Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, United States of America.ORCID 0000-0001-7028-8095
Alyson B HardingDivision of Environmental Health Sciences, School of Public Health, University of Minnesota, Minneapolis, MN, United States of America.ORCID 0000-0003-1171-9777
Samuel JacobsDivision of Environmental Health Sciences, School of Public Health, University of Minnesota, Minneapolis, MN, United States of America.ORCID 0000-0003-2691-0101
M Kumi SmithDivision of Epidemiology & Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, United States of America.ORCID 0000-0001-5861-8100
Timothy R ChurchDivision of Environmental Health Sciences, School of Public Health, University of Minnesota, Minneapolis, MN, United States of America.ORCID 0000-0003-3292-5035
Jesse D BermanDivision of Environmental Health Sciences, School of Public Health, University of Minnesota, Minneapolis, MN, United States of America.
Austin RauDivision of Environmental Health Sciences, School of Public Health, University of Minnesota, Minneapolis, MN, United States of America.
Sato AshidaDepartment of Community and Behavioral Health, College of Public Health, University of Iowa, Iowa City, IA, United States of America.
Marizen R RamirezDivision of Environmental Health Sciences, School of Public Health, University of Minnesota, Minneapolis, MN, United States of America.
University of Minnesota · USUniversity of Iowa · US

Funding

University of Minnesota Clinical and Translational Science Institute (UMN CTSI)UL1TR002494 · NCATS · UNIVERSITY OF MINNESOTA · PI BLAZAR, BRUCE R, WEISDORF, DANIEL J · 2018 to 2022
$34.9M
Minnesota Population Center Science and Technical CoreP2CHD041023 · NICHD · UNIVERSITY OF MINNESOTA · PI THERESA LOUISE OSYPUK · 2016 to 2026
$4.3M
Spatial Analysis CoreR24HD041023 · NICHD · UNIVERSITY OF MINNESOTA TWIN CITIES · PI RUGGLES, STEVE · 2001 to 2016
$4.1M
NCATS NIH HHS UL1 TR002494NICHD NIH HHS P2C HD041023NICHD NIH HHS R24 HD041023
6 · The paper itself

Abstract

Even early in the COVID-19 pandemic, adherence to physical distancing measures was variable, exposing some communities to elevated risk. While cognitive factors from the Health Belief Model (HBM) and resilience correlate with compliance with physical distancing, external conditions may preclude full compliance with physical distancing guidelines. Our objective was to identify HBM and resilience constructs that could be used to improve adherence to physical distancing even when full compliance is not possible. We examined adherence as expressed through 7-day non-work, non-household contact rates in two cohorts: 1) adults in households with children from Minnesota and Iowa; and 2) adults ≥50 years-old from Minnesota, one-third of whom had Parkinson's disease. We identified multiple cognitive factors associated with physical distancing adherence, specifically perceived severity, benefits, self-efficacy, and barriers. However, the magnitude, and occasionally the direction, of these associations was population-dependent. In Cohort 1, perceived self-efficacy for remaining 6-feet from others was associated with a 29% lower contact rate (RR 0.71; 95% CI 0.65, 0.77). This finding was consistent across all race/ethnicity and income groups we examined. The barriers to adherence of having a child in childcare and having financial concerns had the largest effects among individuals from marginalized racial and ethnic groups and high-income households. In Cohort 2, self-efficacy to quarantine/isolate was associated with a 23% decrease in contacts (RR 0.77; 95% CI 0.66, 0.89), but upon stratification by education level, the association was only present for those with at least a Bachelor's degree. Education also modified the effect of the barrier to adherence leaving home for work, increasing contacts among those with a Bachelor's degree and reducing contacts among those without. Our findings suggest that public health messaging tailored to the identified cognitive factors has the potential to improve physical distancing adherence, but population-specific needs must be considered to maximize effectiveness.

Indexed as

COVID-19Physical DistancingAdultChildCognitionCross-Sectional StudiesHumansMiddle AgedPandemicsSARS-CoV-2

Identifiers

PMID35503754
PMCPMC9064111
OpenAlexW4225417701

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.