AN APPLICATION OF GROUP-BASED MODELING APPROACH FOR TRAJECTORY RECOGNITION- THE DEVELOPMENTAL COURSES OF HYPERACTIVITY AND INATTENTIVE SYMPTOMS
Author(s)
Cheng W1, Goodwin R2, Wu P2, Vitaro F3, Tremblay R41Analysis Group, Inc., Boston, MA, USA, 2Columbia University Mailman School of Public Health, New York, NY, USA, 3University of Montreal School of Psycho-Education, Montreal, QC, Canada, 4University of Montreal, Montreal, QC, Canada
OBJECTIVES: Uncertainty remains regarding the developmental courses of inattentive (IN) and hyperactivity (HA) symptoms. Using group-based trajectory modeling, we sought to identify distinct independent and joint IN/HA symptom trajectories and their predictors. METHODS: A total of 1037 boys (mean age: 6.2±0.3 years) from low socioeconomic areas in Montreal were recruited in 1984 for the Longitudinal and Experimental Study of Low Socioeconomic Status (SES) Boys in Montreal. Teacher and mother ratings of subjects’ IN and HA symptoms were collected annually at ages 6, and 10 to 15 using the Social Behavior Questionnaire, where the higher of the two raters’ scores was taken as subject’s IN/HA score. Numbers and probabilities of independent IN and HA trajectories were identified using group-based semi-parametric mixture models. Joint IN/HA trajectories were then constructed as the joint probabilities of independent IN/HA trajectories. Multinomial logistic regressions were conducted to assess baseline parental and subject behavioral problems as predictors of joint trajectories. RESULTS: Six and five independent trajectories were generated for IN and HA symptoms, respectively, constituting 30 joint trajectories. The most common independent IN trajectory (29.5% of study sample) had a moderate number of IN symptoms at baseline that increased slightly with age (moderate-slightly rising), whereas the most common independent HA trajectory (28.5%) was baseline moderate-sharply declining. The most common joint trajectories were based on the co-occurrence of a moderate-sharply rising IN trajectory, and a low-/moderate-slightly rising HA trajectory (17% vs. 14%). Subjects’ aggressiveness, conduct-, oppositional-, and anti-social problems (p<0.001), and paternal SES (p=0.01) were significant predictors of joint trajectories. CONCLUSIONS: Group-based trajectory modeling may be a useful time-dependent pattern recognition tool. It enabled the identification of distinct independent and joint IN/HA trajectories in age-related developmental courses. Assessing baseline behavioral problems and paternal SES may help identify and target interventions for young boys at risk of high-level IN/HA symptoms early on.
Conference/Value in Health Info
2012-06, ISPOR 2012, Washington, D.C., USA
Value in Health, Vol. 15, No. 4 (June 2012)
Code
PMH85
Topic
Methodological & Statistical Research
Topic Subcategory
Modeling and simulation
Disease
Mental Health