BACKGROUND: E-cigarette use poses significant public health concerns, particularly in China, where the market is extensive and the number of users continues to rise. It is essential to explore the beliefs of e-cigarette users, as these often undergo rationalization—a process where individuals reconstruct beliefs to justify their behavior amid cognitive dissonance. For users, this may lead to minimizing health risks or adopting misconceptions about e-cigarette use. Investigating rationalization beliefs is crucial for developing targeted public health interventions and educational strategies that effectively address the unique context of e-cigarette consumption in China.This study aims to develop a scale measuring rationalization beliefs among e-cigarette users in China, providing a reliable tool for future research and interventions.
METHODS: The Rationalization Belief Scale for E-cigarette Users was developed through a systematic process. First, a literature review and semi-structured interviews with 25 e-cigarette users were conducted, using thematic analysis to identify key rationalization beliefs. A preliminary scale was created and refined through a small-scale pre-test. The finalized questionnaire was then distributed via a snowball sampling approach, yielding 617 valid responses. Psychometric evaluation included exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) to assess structural validity and reliability.
RESULTS: The final version of the scale comprised 28 items loading onto four factors identified through EFA: Harm Skepticism Beliefs, Comparative Safety Beliefs, Vaping Function Beliefs, and Social Acceptability Beliefs, which explained 57.9% of the variance. The overall scale demonstrated high internal consistency (Cronbach's α = 0.936). The reliability of the subscales ranged from 0.774 to 0.911. CFA confirmed a good fit to the data (CFI = 0.914, TLI = 0.906, RMSEA = 0.059).
CONCLUSIONS: We constructed a valid and reliable instrument for measuring rationalization beliefs among e-cigarette users. This scale can facilitate further research into personalized behavior intervention and inform public health strategies aimed at reducing e-cigarette usage.