Development, Ecology, and Prevention of Adult Addictive Behavior

6. 项目总结/文摘

6. Project Summary/Abstract The proposed revised application would continue research on a sample of 999 multiethnic adults who were longitudinally assessed from ages 11-12 to 23-24. Assessment included a CIDI diagnostic interview at age 18-19 and coded videotaped observations of adolescent family and peer interactions. The sample was individually randomized to the Family Check-Up model in adolescence, which yielded long-term effects on drug use, antisocial behavior, depression, and academic success. The proposed follow-up assessment at age 26- 27 would include the CIDI diagnostic interview on addictive behavior and psychopathology, time allocation to high- versus low-investment activities, peer network, self-regulation, and the collection of DNA in saliva samples. Three approaches to genotyping are proposed, including candidate gene, gene family, and novel gene exploration by a team of investigators currently studying the molecular genetics of addictive behavior. These data will be used to address the following hypotheses: (a) the disrupted self-regulation hypothesis, that adult problem behavior generally and addictive behavior specifically are part of an overall pattern of adaptation that is characterized by a low-investment strategy in respect to family relationships and other adult milestones, with low demands on self-regulation; (b) the genetic moderation hypothesis, indicating that the effects of poor parental monitoring and deviant peer exposure on progressions in AOD use and other problem behaviors are most pronounced for youth who are genetically vulnerable; and (c) the risk malleability hypothesis, which proposes that early environmental risk can be modified and that these effects are especially pronounced for genetically prone youth. Testing of all 3 sets of hypotheses requires examination of longitudinal data from early adolescence through age 26-27 that uses a variety of advanced analytic strategies, including trajectory analyses, latent profile analysis, latent growth modeling, and complier average causal effect modeling for examining the effects of the Family Check-Up on risk exposure.