Evidence map›Paper›PMID 36368238›Full record

ArticleSocial science & medicine (1982)2022

State mask mandates and psychological reactance theory: The role of political partisanship and COVID-19 risk in mask adoption and resistance.

Stephen A Rains, Paulina M Colombo, Brian L Quick, Lauren A Kriss

Abstract read
In one paragraph

Article in Social science & medicine (1982), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
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  5. Article
  6. The Effectiveness of Face Mask Mandates on COVID-19 Transmission in Utah.Public health reports (Washington, D.C. : 1974) · 2024
    Article
  7. 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

4 authors.

Stephen A RainsUniversity of Arizona, USA. Electronic address: srains@email.arizona.edu.
Paulina M ColomboUniversity of Arizona, USA.
Brian L QuickUniversity of Illinois, USA.
Lauren A KrissUniversity of Wisconsin, Madison, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

rationalePsychological reactance theory was applied to examine the implications of state-level mask mandates in the United States during the COVID-19 pandemic. We evaluated the role of political partisanship and COVID-19 risk on changes in self-reported mask wearing before and after the imposition and removal of state mask mandates.

methodSecondary data from several sources were aggregated about self-reported mask wearing behavior, state mandates, COVID-19 infection rates, and state-level political partisanship. Difference-in-differences tests were performed using logistic regression to evaluate whether change in mask wearing behavior following the imposition or removal of a mandate was greater in states based on state-level political partisanship and COVID-19 infection rates.

resultsAlthough mask adoption generally increased following mandates, the amount of increase was smaller in more Republican states compared to more Democratic states. Mask wearing generally decreased following the removal of mandates, with greater decreases when COVID-19 infection rates were lower.

conclusionThe results collectively offer insights about the nuanced role of contextual factors in the adoption and resistance to masks following state mask mandates. Partisanship was important in responses to the imposition of state mask mandates and COVID-19 risk played a critical role in responses to mandate removal.

Indexed as

COVID-19HumansPandemicsPsychological TheorySelf ReportCOVID-19Governmental mask mandatesMask adoptionMask resistancePolitical partisanshipPsychological reactancePublic health

Identifiers

PMID36368238
PMCPMC9616476

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.