ArticleJournal of biometrics & biostatistics2012
Estimating Transitional Probabilities with Cross-Sectional Data to Assess Smoking Behavior Progression: A Validation Analysis.
Article in Journal of biometrics & biostatistics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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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
5 citing papers in PubMed.
- Estimating of Net Transition Probabilities in Triple Stages of Cigarette Consumption in Iranian Men.Tanaffos · 2018Article
- Dynamic transitions between marijuana use and cigarette smoking among US adolescents and emerging adults.The American journal of drug and alcohol abuse · 2018Article
- A framework for evaluating the public health impact of e-cigarettes and other vaporized nicotine products.Addiction (Abingdon, England) · 2017Review
- Modeling Drinking Behavior Progression in Youth with Cross-sectional Data: Solving an Under-identified Probabilistic Discrete Event System.Current HIV research · 2016Article
- Estimating the Transitional Probabilities of Smoking Stages with Cross-sectional Data and 10-Year Projection for Smoking Behavior in Iranian Adolescents.International journal of preventive medicine · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
BACKGROUND AND
objectiveNew analytical tools are needed to advance tobacco research, tobacco control planning and tobacco use prevention practice. In this study, we validated a method to extract information from cross-sectional survey for quantifying population dynamics of adolescent smoking behavior progression.
methodsWith a 3-stage 7-path model, probabilities of smoking behavior progression were estimated employing the Probabilistic Discrete Event System (PDES) method and the cross-sectional data from 1997-2006 National Survey on Drug Use and Health (NSDUH). Validity of the PDES method was assessed using data from the National Longitudinal Survey of Youth 1997 and trends in smoking transition covering the period during which funding for tobacco control was cut substantively in 2003 in the United States.
resultsProbabilities for all seven smoking progression paths were successfully estimated with the PDES method and the NSDUH data. The absolute difference in the estimated probabilities between the two approaches varied from 0.002 to 0.076 (p>0.05 for all) and were highly correlated with each other (
conclusionsThe PDES method has validity in quantifying population dynamics of smoking behavior progression with cross-sectional survey data. The estimated transitional probabilities add new evidence supporting more advanced tobacco research, tobacco control planning and tobacco use prevention practice. This method can be easily extended to study other health risk behaviors.
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Registered trials
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