ArticlePreventive medicine2017
Cigarette smoking risk-reducing beliefs: Findings from the United States Health Information National Trends Survey.
Article in Preventive medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 6 papers.
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.
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.
Who cites it
6 citing papers in PubMed, 7 citations in OpenAlex.
- Observational
- Perceptions and Patterns of Cigarette and E-Cigarette Use among Hispanics: A Heterogeneity Analysis of the 2017-2019 Health Information National Trends Survey.International journal of environmental research and public health · 2021Article
- Psychosocial determinants of quit motivation in older smokers from deprived backgrounds: a cross-sectional survey.BMJ open · 2021Article
- Knowledge and attitudes toward cigarette and narghile smoking among previous smokers in Lebanon.Environmental science and pollution research international · 2020Article
- Examining outcome expectancies for smoking vs. abstinence among adult daily smokers.Addictive behaviors · 2020Article
- Pilot study to inform young adults about the risks of electronic cigarettes through text messaging.Addictive behaviors reports · 2019Article
Corrections and comments
- Erratum issued
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
Cigarette smoking risk-reducing beliefs are ideas that certain health promoting behaviors (e.g., exercise) may mitigate the risks associated with smoking. The objective of this study was to describe smoking risk-reducing beliefs and the belief that quitting can reduce the harmful effects of smoking among the U.S. adult population and the associations between these beliefs, current smoking status, and sociodemographics. Data were from the Health Information National Trends Survey 4 (HINTS 4) Cycles 3 and 4 (2013-2014; N=6862). Descriptive analyses were conducted to examine bivariate associations among the quit smoking belief, smoking risk-reducing beliefs, and covariates. Weighted ordinal logistic regression models examined the adjusted associations between smoking status and sociodemographics, with quit smoking belief and risk-reducing beliefs. Eighty-two percent of the population reported that quitting cigarette smoking can help reduce the harmful effects of smoking a lot: former smokers and individuals with higher educational attainment were more likely to endorse this belief than never smokers and those with lower educational attainment. Many people endorsed smoking risk-reducing beliefs about exercise (79.3%), fruits and vegetables (71.8%), vitamins (67.2%), and sleep (68.5%). Former smokers were less likely to subscribe to these beliefs than never smokers. Vulnerable populations who may be most at risk of smoking attributable morbidity and mortality were more likely to endorse risk-reducing beliefs. Future studies are needed to better understand how risk-reducing beliefs are formed and if modifying these beliefs may help to reduce cigarette smoking in the U.S.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.