利用计划行为理论预测青少年国际电子烟用户的DIY电子烟混合。

Rachael A Record, Maxwell Groznik, Mark A Sussman
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引用次数: 0

摘要

背景:年轻人使用电子尼古丁输送系统(ENDS)和自己动手(DIY)混合电子果汁的趋势在世界各地都在增长。研究嵌入在主要行为(如吸电子烟)中的次要行为(如混合)的理论框架是有限的,这导致了对行为表现的学术理解的挑战。本研究通过对计划行为理论(TPB)的多重行为测试,探讨了终端用户混合DIY电子果汁决策的理论驱动因素。方法:从多产公司招募了18-19岁的国际青年参与者(n=203)进行在线横断面调查。路径建模测试了四种理论驱动模型来探索混合的行为性能。研究结果:数据支持TPB预期,并揭示了次要行为的新途径。对态度、规范和意图的初级知觉可以预测同样的次级知觉。此外,对于主要和次要行为,感知规范是感知态度的函数。对于次要行为,规范性影响是通过感知态度间接体验的。结论:DIY电子果汁混合是对混合的感知态度和行为控制以及对一般终端使用的感知态度、规范和意图的产物。虽然不受管制的DIY实验在年轻人中有所增加,但这些发现为寻求普及和减少使用的公共卫生努力提供了一个视角。了解DIY电子果汁的行为对于预测囤积行为和业余实验的负面结果至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Using the Theory of Planned Behavior to Anticipate DIY E-juice Mixing among Young Adult International E-cigarette Users.

Using the Theory of Planned Behavior to Anticipate DIY E-juice Mixing among Young Adult International E-cigarette Users.

Using the Theory of Planned Behavior to Anticipate DIY E-juice Mixing among Young Adult International E-cigarette Users.

Using the Theory of Planned Behavior to Anticipate DIY E-juice Mixing among Young Adult International E-cigarette Users.

Background: Trends in young adult use of electronic nicotine delivery systems (ENDS) and experimentation with do-it-yourself (DIY) e-juice mixing are growing around the world. Theoretical frameworks for examining secondary behaviors (i.e., mixing) embedded within a primary behavior (i.e., vaping) are limited, leading to challenges in scholarly understanding of behavioral performance. This study explored the theoretically driven factors surrounding ENDS users' decision to mix DIY e-juice through a multiple behavior test of the theory of planned behavior (TPB).

Methods: An international sample of young adult participants aged 18-19 (n=203) was recruited from Prolific for an online crosssectional survey. Path modeling tested four theoretically driven models to explore behavioral performance of mixing.

Findings: The data supported TPB expectations and revealed new paths for secondary behavior. Primary perceptions of attitudes, norms, and intention were predictive of the same secondary perceptions. In addition, for both primary and secondary behaviors, perceived norms were a function of perceived attitudes. For the secondary behavior, normative influence was experienced indirectly through perceived attitudes.

Conclusion: DIY e-juice mixing is a product of perceived attitudes and behavioral control surrounding mixing as well as perceived attitudes, norms, and intention surrounding general ENDS use. While unregulated DIY experimentation increases among youth, these findings provide a lens for public health efforts seeking to reach and reduce use. Understanding DIY e-juice behaviors is essential to anticipate stockpiling behaviors and negative outcomes from amateur experimentation.

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