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Validating E-Cigarette Dependence Scales Based on Dynamic Patterns of Vaping Behaviors.
Buu, Anne; Cai, Zhanrui; Li, Runze; Wong, Su-Wei; Lin, Hsien-Chang; Su, Wei-Chung; Jorenby, Douglas E; Piper, Megan E.
  • Buu A; Department of Health Promotion and Behavioral Sciences, University of Texas Health Science Center, Houston, TX, USA.
  • Cai Z; Department of Statistics, Pennsylvania State University, University Park, PA, USA.
  • Li R; Department of Statistics, Pennsylvania State University, University Park, PA, USA.
  • Wong SW; Department of Health Promotion and Behavioral Sciences, University of Texas Health Science Center, Houston, TX, USA.
  • Lin HC; Department of Applied Health Science, School of Public Health, Indiana University, Bloomington, IN, USA.
  • Su WC; Department of Epidemiology, Human Genetics & Environmental Sciences, University of Texas Health Science Center, Houston, TX, USA.
  • Jorenby DE; Center for Tobacco Research & Intervention, University of Wisconsin, Madison, WI, USA.
  • Piper ME; Center for Tobacco Research & Intervention, University of Wisconsin, Madison, WI, USA.
Nicotine Tob Res ; 23(9): 1484-1489, 2021 08 18.
Article en En | MEDLINE | ID: mdl-33758949
ABSTRACT

INTRODUCTION:

Existing e-cigarette dependence scales are mainly validated based on retrospective overall consumption or perception. Further, given that the majority of adult e-cigarette users also use combustible cigarettes, it is important to determine whether e-cigarette dependence scales capture the product-specific dependence. This study fills in the current knowledge gaps by validating e-cigarette dependence scales using novel indices of dynamic patterns of e-cigarette use behaviors and examining the association between dynamic patterns of smoking and e-cigarette dependence among dual users.

METHODS:

Secondary analysis was conducted on the 2-week ecological momentary assessment data from 116 dual users. The Smoothly Clipped Absolute Deviation penalty (SCAD) was adopted to select important indices for dynamic patterns of consumption or craving and estimate their associations with e-cigarette dependence scales.

RESULTS:

The fitted linear regression models support the hypothesis that higher e-cigarette dependence is associated with higher levels of e-cigarette consumption and craving as well as lower instability of e-cigarette consumption. Controlling for dynamic patterns of vaping, dual users with lower e-cigarette dependence tend to report higher day-to-day dramatic changes in combustible cigarette consumption but not higher average levels of smoking.

CONCLUSIONS:

We found that more stable use patterns are related to higher levels of dependence, which has been demonstrated in combustible cigarettes and we have now illustrated in e-cigarettes. Furthermore, the e-cigarette dependence scales may capture the product-specific average consumption but not product-specific instability of consumption. IMPLICATIONS This study provides empirical support for three e-cigarette dependence

measures:

PS-ECDI, e-FTCD, and e-WISDM, based on dynamic patterns of e-cigarette consumption and craving revealed by EMA data that have great ecological validity. This is the first study that introduces novel indices of dynamic patterns and demonstrates their potential applications in vaping research.
Asunto(s)

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Productos de Tabaco / Sistemas Electrónicos de Liberación de Nicotina / Vapeo Tipo de estudio: Observational_studies / Risk_factors_studies Límite: Adult / Humans Idioma: En Año: 2021 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Productos de Tabaco / Sistemas Electrónicos de Liberación de Nicotina / Vapeo Tipo de estudio: Observational_studies / Risk_factors_studies Límite: Adult / Humans Idioma: En Año: 2021 Tipo del documento: Article