Refining the tobacco dependence phenotype using the Wisconsin Inventory of Smoking Dependence Motives.

Abstract

The construct of tobacco dependence is important from both scientific and public health perspectives, but it is poorly understood. The current research integrates person-centered analyses (e.g., latent profile analysis) and variable-centered analyses (e.g., exploratory factor analysis) to understand better the latent structure of dependence and to guide distillation of the phenotype. Using data from four samples of smokers (including treatment and non-treatment samples), latent profiles were derived using the Wisconsin Inventory of Smoking Dependence Motives (WISDM) subscale scores. Across all four samples, results revealed a unique latent profile that had relative elevations on four dependence motive subscales (Automaticity, Craving, Loss of Control, and Tolerance). Variable-centered analyses supported the uniqueness of these four subscales both as measures of a common factor distinct from that underlying the other nine subscales, and as the strongest predictors of relapse, withdrawal and other dependence criteria. Conversely, the remaining nine motives carried little unique predictive validity regarding dependence. Applications of a factor mixture model further support the presence of a unique class of smokers in relation to a common factor underlying the four subscales. The results illustrate how person-centered analyses may be useful as a supplement to variable-centered analyses for uncovering variables that are necessary and/or sufficient predictors of disorder criteria, as they may uncover small segments of a population in which the variables are uniquely distributed. The results also suggest that severe dependence is associated with a pattern of smoking that is heavy, pervasive, automatic and relatively unresponsive to instrumental contingencies.

Smoking Behavior: A Cross-Sectional Study to Assess the Dimensionality of the Brief Wisconsin Inventory of Smoking Dependence Motives and Identify Different Typologies Among Young Daily Smokers

“…These groups differed qualitatively, mainly in the relationship between PDMs and SDMs: whereas Group B had similar levels for the subscales included in both constructs, Group A tended to have higher levels of SDMs than PDMs. This result was consistent with the study of Piper et al, 15 in which PDM and SDM were emphasized for the first time with a person-centered analysis. The authors identified five motivational profiles using the WISDM.…”

“…The second aim was to identify types of smokers using the B-WISDM. We expected to observe profiles similar to those identified by Piper et al 15 using the WISDM. Motivational typologies were then compared for smoking behavior indices.…”

“…In order to achieve this goal, a cluster analysis was performed using the software SLEIPNER 2.1. 43 Even though Piper et al 15 used a latent profile analysis (LPA), cluster analysis was preferred because the assumption of local independence was considered too hard: covariances of the variables included in the analysis might not be explained just by class membership (as prescribed for LPA) but also by the two high-ordered dimensions found for the WISDM 15 and hypothesized for the B-WISDM. Asendorpf et al 44 suggested the adoption of a two-step clustering procedure: initially using Ward's hierarchical method 45 followed by a nonhierarchical K-means method.…”

“…In several studies, the WISDM has demonstrated good psychometric properties, such as good internal consistency and concurrent, discriminant, and predictive validity. [10][11][12][13][14][15][16][17] Through an extensive psychometric analysis, Piper et al 15 noted the presence of two synthetic WISDM scales, namely primary dependence motives (PDM) and secondary dependence motives (SDM). PDM is composed of four scales (automaticity, craving, loss of control, and tolerance) and represents the core component of tobacco dependence, whereas SDM is composed of the nine remaining scales.…”

Psychometric Characteristics of the Brief Wisconsin Inventory of Smoking Dependence Motives Among a Nonclinical Sample of Smokers

“…This measure, which identifies 13 theoretically driven subscales encompassing the physiological, psychological, and social dimensions that drive nicotine dependence, also has good psychometric properties including concurrent, discriminant, and predictive validity. [12][13][14] Further research has parsed the subscales into two broader categories-primary dependence motives (PDMs) and secondary dependence motives (SDMs)-that underscore the core and ancillary features of tobacco and nicotine dependence, respectively. 13 Given the length and assessment burden associated with administering the full 68-item measure, Smith and colleagues 15 refined the measure to a 37-item Brief WISDM.…”