Literature DB >> 12324173

Assessing tobacco beliefs among youth using item response theory models.

A T Panter1, Bryce B Reeve.   

Abstract

Successful intervention research programs to prevent adolescent smoking require well-chosen, psychometrically sound instruments for assessing smoking prevalence and attitudes. Twelve thousand eight hundred and ten adolescents were surveyed about their smoking beliefs as part of the Teenage Attitudes and Practices Survey project, a prospective cohort study of predictors of smoking initiation among US adolescents. Item response theory (IRT) methods are used to frame a discussion of questions that a researcher might ask when selecting an optimal item set. IRT methods are especially useful for choosing items during instrument development, trait scoring, evaluating item functioning across groups, and creating optimal item subsets for use in specialized applications such as computerized adaptive testing. Data analytic steps for IRT modeling are reviewed for evaluating item quality and differential item functioning across subgroups of gender, age, and smoking status. Implications and challenges in the use of these methods for tobacco onset research and for assessing the developmental trajectories of smoking among youth are discussed.

Entities:  

Mesh:

Year:  2002        PMID: 12324173     DOI: 10.1016/s0376-8716(02)00213-2

Source DB:  PubMed          Journal:  Drug Alcohol Depend        ISSN: 0376-8716            Impact factor:   4.492


  6 in total

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Authors:  Maria Orlando Edelen
Journal:  Nicotine Tob Res       Date:  2014-09       Impact factor: 4.244

2.  Analyzing differences between parent- and self-report measures with a latent space approach.

Authors:  Dongyoung Go; Minjeong Jeon; Saebyul Lee; Ick Hoon Jin; Hae-Jeong Park
Journal:  PLoS One       Date:  2022-06-29       Impact factor: 3.752

3.  Using an item response model to examine the nicotine dependence construct as characterized by the HONC and the mFTQ among adolescent smokers.

Authors:  Laura MacPherson; David R Strong; Mark G Myers
Journal:  Addict Behav       Date:  2008-02-20       Impact factor: 3.913

4.  Modeling nicotine dependence: an application of a longitudinal IRT model for the analysis of adolescent nicotine dependence syndrome scale.

Authors:  Li C Liu; Donald Hedeker; Robin J Mermelstein
Journal:  Nicotine Tob Res       Date:  2012-05-13       Impact factor: 4.244

5.  A new adaptive testing algorithm for shortening health literacy assessments.

Authors:  Sasikiran Kandula; Jessica S Ancker; David R Kaufman; Leanne M Currie; Qing Zeng-Treitler
Journal:  BMC Med Inform Decis Mak       Date:  2011-08-06       Impact factor: 2.796

6.  A GPU-Based Gibbs Sampler for a Unidimensional IRT Model.

Authors:  Yanyan Sheng; William S Welling; Michelle M Zhu
Journal:  Int Sch Res Notices       Date:  2014-10-30
  6 in total

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