title: Analysis of transtheoretical model of health behavioral changes in a nutrition intervention study--a continuous time Markov chain model with Bayesian approach.
abstract: Continuous time Markov chain (CTMC) models are often used to study the progression of chronic diseases in medical research but rarely applied to studies of the process of behavioral change. In studies of interventions to modify behaviors, a widely used psychosocial model is based on the transtheoretical model that often has more than three states (representing stages of change) and conceptually permits all possible instantaneous transitions. Very little attention is given to the study of the relationships between a CTMC model and associated covariates under the framework of transtheoretical model. We developed a Bayesian approach to evaluate the covariate effects on a CTMC model through a log-linear regression link. A simulation study of this approach showed that model parameters were accurately and precisely estimated. We analyzed an existing data set on stages of change in dietary intake from the Next Step Trial using the proposed method and the generalized multinomial logit model. We found that the generalized multinomial logit model was not suitable for these data because it ignores the unbalanced data structure and temporal correlation between successive measurements. Our analysis not only confirms that the nutrition intervention was effective but also provides information on how the intervention affected the transitions among the stages of change. We found that, compared with the control group, subjects in the intervention group, on average, spent substantively less time in the precontemplation stage and were more/less likely to move from an unhealthy/healthy state to a healthy/unhealthy state.
authors.affiliation: Department of Biostatistics, The University of Texas Health Science Center, 1200 Pressler Street, Houston, 77030, Texas, U.S.A.|Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, 77030, Texas, U.S.A.
authors.forename: Junsheng
authors.initials: J
authors.lastname: Ma
authors.affiliation: Department of Biostatistics, The University of Texas Health Science Center, 1200 Pressler Street, Houston, 77030, Texas, U.S.A.
authors.forename: Wenyaw
authors.initials: W
authors.lastname: Chan
authors.affiliation: Department of Emergency Medicine, Harvard Medical School, Boston, 02115, MA, U.S.A.
authors.forename: Chu-Lin
authors.initials: CL
authors.lastname: Tsai
authors.affiliation: Department of Biostatistics, The University of Texas Health Science Center, 1200 Pressler Street, Houston, 77030, Texas, U.S.A.
authors.forename: Momiao
authors.initials: M
authors.lastname: Xiong
authors.affiliation: Department of Biostatistics, The University of Texas Health Science Center, 1200 Pressler Street, Houston, 77030, Texas, U.S.A.
authors.forename: Barbara C
authors.initials: BC
authors.lastname: Tilley
mesh_terms: D000368:Aged; D001499:Bayes Theorem; D036262:Empirical Research; D005247:Feeding Behavior; D005260:Female; D015438:Health Behavior; D006801:Humans; D016014:Linear Models; D008297:Male; D008390:Markov Chains; D008875:Middle Aged; D008960:Models, Psychological; D011795:Surveys and Questionnaires
keywords: Bayesian data analysis; Markov chain models; Metropolis-Hastings algorithm; covariates; transtheoretical models