Evidence map›Paper›PMID 34032383›Full record

ArticleApplied psychology. Health and well-being2021

Adhering to COVID-19 health guidelines: Examining demographic and psychological predictors of adherence.

Brooklynn Bailey, Megan L Whelen, Daniel R Strunk

Abstract read
In one paragraph

Article in Applied psychology. Health and well-being, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

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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

3 authors.

Brooklynn BaileyDepartment of Psychology, Ohio State University, Columbus, OH, USA.ORCID 0000-0001-6656-0607
Megan L WhelenDepartment of Psychology, Ohio State University, Columbus, OH, USA.ORCID 0000-0001-7428-5502
Daniel R StrunkDepartment of Psychology, Ohio State University, Columbus, OH, USA.ORCID 0000-0002-7444-0741

Funding

The Ohio State University Office of Research
6 · The paper itself

Abstract

The effort to limit the spread of the coronavirus (COVID-19) has relied heavily on the general public's compliance with health guidelines limiting social contact and mitigating risk when contact occurs. The aim of this study was to identify latent variables underlying adherence to COVID-19 guidelines and to examine demographic and psychological predictors of adherence. A sample of US adults (N = 1,200) were surveyed in late April to mid-May 2020. The factor structure of adherence was examined using exploratory factor analysis. Machine learning regression models using elastic net regularization were used to examine predictors of adherence. Two factors characterized adherence: avoidance and cleaning. Elastic net models identified differential demographic and psychological predictors of these two forms of adherence. Religious affiliation, denial coping, full-time employment, substance use coping, and being 60 or older predicted lower avoidance adherence. Behavioral and mindfulness emotion regulation skills, agreeableness, and Democrat political affiliation predicted greater avoidance adherence. For cleaning adherence, interpersonal and behavioral emotion regulation skills and conscientiousness emerged as strong predictors of greater cleaning. Efforts to promote compliance with COVID-19 health guidelines may benefit from distinguishing avoidance and cleaning adherence and considering predictors of each of these aspects of adherence.

Indexed as

COVID-19Adaptation, PsychologicalAdultDemographyGuideline AdherenceHumansSARS-CoV-2COVID-19health adherencehealth behaviorsmachine learning

Identifiers

PMID34032383
PMCPMC8239601

What OpenQuestion holds

Textmetadata
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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.