Evidence map›Paper›PMID 37793477›Full record

ArticlePreventive medicine2023

Differences in health care provider screening for tobacco use among youth in the United States: The National Youth Tobacco Survey, 2021.

Osayande Agbonlahor, Delvon T Mattingly, Jayesh Rai, Joy L Hart, Alison C McLeish, Kandi L Walker

Abstract read
In one paragraph

Article in Preventive medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

6 authors.

Osayande AgbonlahorDepartment of Communication, College of Arts and Sciences, University of Louisville, Louisville, KY, USA; Christina Lee Brown Envirome Institute, School of Medicine, University of Louisville, Louisville, KY, USA.
Delvon T MattinglyDepartment of Behavioral Science, College of Medicine, University of Kentucky, Lexington, KY, USA; Center for Health Equity Transformation, College of Medicine, University of Kentucky, Lexington, KY, USA.
Jayesh RaiCollege of Medicine, University of Cincinnati, Cincinnati, OH, USA.
Joy L HartDepartment of Communication, College of Arts and Sciences, University of Louisville, Louisville, KY, USA; Christina Lee Brown Envirome Institute, School of Medicine, University of Louisville, Louisville, KY, USA; American Heart Association Tobacco Center for Regulatory Science, Dallas, TX, USA. Electronic address: joy.hart@louisville.edu.
Alison C McLeishChristina Lee Brown Envirome Institute, School of Medicine, University of Louisville, Louisville, KY, USA; American Heart Association Tobacco Center for Regulatory Science, Dallas, TX, USA; Department of Psychological and Brain Sciences, University of Louisville, Louisville, KY, USA.
Kandi L WalkerDepartment of Communication, College of Arts and Sciences, University of Louisville, Louisville, KY, USA; Christina Lee Brown Envirome Institute, School of Medicine, University of Louisville, Louisville, KY, USA; American Heart Association Tobacco Center for Regulatory Science, Dallas, TX, USA.

Funding

ConProject-006U54HL120163 · NHLBI · AMERICAN HEART ASSOCIATION · PI BHATNAGAR, ARUNI, ROBERTSON, ROSE MARIE · 2018 to 2022
$18.8M
NHLBI NIH HHS U54 HL120163
6 · The paper itself

Abstract

objectiveHealth care providers (HCP) are encouraged to screen youth for tobacco product use as a key step in preventing such use and associated health outcomes. However, recent data examining differences in HCP tobacco screening by sociodemographic characteristics and tobacco use is scant.

methodsData from the 2021 National Youth Tobacco Survey (N = 14,685) were analyzed. Three types of HCP screening were examined: no screening, any e-cigarette use (e-cigarette only, e-cigarette and other tobacco), and non-e-cigarette tobacco product use. Differences by HCP screening were examined using multinomial logistic regression adjusted for age, sex, gender identity, sexual orientation, race/ethnicity, and tobacco use (non-current, sole, dual/poly).

resultsAmong the sample, 42.8% were screened for any tobacco use, with 30.6% screened for any e-cigarette use and 12.2% for non-e-cigarette tobacco product use only. Youth who were older (vs. younger) (OR = 5.98, 95% CI: 4.78-7.49) and gay/lesbian (vs. heterosexual) (OR = 1.47, 95% CI: 1.02-2.12) were more likely to be screened for e-cigarette use. Youth who were non-Hispanic Black (vs. non-Hispanic White) were less likely to be screened for e-cigarette use (OR = 0.53, 95% CI: 0.42-0.67) and more likely to be screened for non-e-cigarette tobacco use (OR = 1.34, 95% CI: 1.10-1.63). Current sole tobacco use (vs. non-current use) and dual/poly tobacco use (vs. non-current use) increased the likelihood for HCP screening for e-cigarette use.

conclusionsThe majority of U.S. youth continue to not be screened for tobacco use by their HCP. Evidence of disparities in tobacco use screening suggest the need for policies and training that promote equity in screening.

Indexed as

Electronic Nicotine Delivery SystemsTobacco ProductsTobacco Use DisorderAdolescentFemaleGender IdentityHumansMaleTobacco UseUnited StatesE-cigarettesHealth care provider screeningSociodemographicsTobaccoYouth

Identifiers

PMID37793477
PMCPMC10681140

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.