Evidence map›Paper›PMID 32981125›Full record

ArticlePublic health nursing (Boston, Mass.)2020

Perceived risk of infection and smoking behavior change during COVID-19 in Ohio.

Ilana R Azulay Chertok

Open access · bronzeAbstract read
In one paragraph

Article in Public health nursing (Boston, Mass.), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed, 2 pooled it
6.3field-weighted citation impact, top 3% 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

33 citing papers in PubMed, 2 syntheses or guidelines pooled it, 61 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

1 author at 1 institution in 1 country.

Ilana R Azulay ChertokSchool of Nursing, Ohio University, Athens, OH, USA.ORCID 0000-0001-7767-2081
Ohio University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThe recent COVID-19 pandemic may catalyze smoking behavior modification. The purpose of the study was to examine factors associated with reducing smoking exposure during the COVID-19 outbreak.

designCross-sectional design using the Health Belief Model to develop an online survey distributed throughout Ohio early during the outbreak. SAMPLE: 810 adults in Ohio (77.9% non-smokers, 22.1% current smokers). MEASUREMENTS: Sociodemographic factors, smoking and behavior changes since the COVID-19 outbreak, and perceived risk of infection were collected. Logistic regression analyses were conducted to determine factors associated with indoor smoking bans and factors associated with desire to quit smoking since the outbreak.

resultsFor the overall sample, the odds of indoor smoking bans were significantly associated with never smoked, college education, single-family residence, not living with smokers, and perceived importance of avoiding public places. For smokers, the desire to quit smoking since the COVID-19 outbreak was associated with diabetes and perceived risk of severe infection.

conclusionsIdentified factors inform residential smoking exposure reduction through indoor smoking bans. Having an increased perceived risk of severe infection among smokers may motivate cessation. Public health nurses can provide accurate and accessible resources for smoking cessation during the COVID-19 pandemic to promote healthy lifestyle modification.

Indexed as

Health Knowledge, Attitudes, PracticePandemicsAdolescentAdultCOVID-19Cross-Sectional StudiesFemaleHealth Belief ModelHumansMaleMiddle AgedOhioPublic Health NursingRisk AssessmentSmokingSmoking Cessationepidemicpandemicsmoking

Identifiers

PMID32981125
PMCPMC7537299
OpenAlexW3087887438

What OpenQuestion holds

Textmetadata
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.