Modeling nicotine dependence: an application of a longitudinal IRT model for the analysis of adolescent nicotine dependence syndrome scale.

Abstract

Measures of nicotine dependence typically use the item average or total score from rating scales, such as the Nicotine Dependence Syndrome Scale (NDSS). Alternatively, item response theory (IRT) methods can provide useful item-specific information. IRT methods developed for longitudinal data can additionally provide information about item-specific changes over time. We describe a longitudinal 2-parameter ordinal IRT model, and compare the results from this model with those from an IRT model for only the baseline item responses, and a conventional longitudinal analysis of the item-average NDSS score. We examined a 10-item, adolescent version of the NDSS at baseline, 6, 15, and 24 months for 1,097 9th or 10th graders. IRT analysis of the baseline data revealed that the items "willing to go out of the house in a storm to find a cigarette," "choose to spend money on cigarettes than lunch," "function better after morning cigarette," and "worth smoking in cold or rain," were good items at distinguishing individuals' levels of nicotine dependency. While the analysis of the averaged NDSS score indicated linear growth over time, the longitudinal IRT method revealed that only 5 out of the 10 items showed statistical increase over time. Infrequently endorsed NDSS items were generally better able to distinguish higher levels of dependency. The endorsement of such items increased over time. Items that changed significantly over time reflected the general drive concept of dependence, as well as the total first overarching dimension of dependence.