The Modified Cigarette Evaluation Questionnaire: Psychometric properties of the originally-proposed five-factor structure and a novel four-factor structure for use with adults who currently smoke cigarettes

Background: The Modified Cigarette Evaluation Questionnaire (MCEQ) measures self-reported, subjective rein -forcing and aversive effects of smoking. The MCEQ is proposed as comprising five factors. However, its latent factor structure has been confirmed in only one published study, and key psychometric properties like mea-surement invariance and test-criterion validity have not been formally examined.Methods: We examined the latent structure of the MCEQ using confirmatory and exploratory factor analysis and evaluated internal consistency, measurement invariance, between-group differences, and relationships with smoking-related characteristics in a sample of 764 adults who smoke cigarettes. As a secondary test of construct validity, we fit identified latent factor structures to a sample of 131 adults from a prior trial who were biochemically-confirmed to currently smoke.Results: A four-factor structure that recently was validated for an e-cigarette-adapted version of the MCEQ outperformed the originally-proposed five-factor structure in several ways: it uniquely evidenced good model fit both within the primary and replication samples, reached scalar invariance for all participant subgroups tested, was sensitive to detecting numerous between-groups differences in subsamples of interest, and each of its sub-scales was associated with at least one smoking characteristic assessed.Conclusions: The four-factor MCEQ structure evidenced stronger psychometric properties in our sample than did the original five-factor MCEQ. However, until additional research is conducted on the utility of the five-and four-factor solutions in other samples, neither the five-nor the four-factor MCEQ structure should be assumed. In the meantime, researchers should examine the MECQ's latent structure in their data prior to conducting subsequent analyses.