بزهکاری و اختلال رانندگی با الکل در میان مردان جوان: مطالعه طولی

Abstract The present study assessed how the trajectory of delinquency affects the growth curve of alcohol-impaired driving using three-waves of data collected from the Buffalo Longitudinal Survey of Young Men (BLSYM). Using the structural equation modeling method, latent growth modeling was utilized to assess four age cohorts of sixteen, seventeen, eighteen, and nineteen years of age at the first wave. The data indicated that the growth rate of delinquency significantly and positively affects the growth rate of alcohol-impaired driving for the respondents who were sixteen at the first wave. The growth rate of drinking was also significantly and positively associated with the growth rate of alcohol-impaired driving for this age cohort. Although the growth rate of delinquency had no significant effect on the growth rate of alcohol-impaired driving for the age cohort which was seventeen at Wave 1, the growth rates of both drinking and drug use did affect for this age cohort. The data, however, showed that alcohol-impaired driving had a significant increase across the waves for the eighteen year old cohort, but there was no significant variation in the rate across respondents. Finally, for the nineteen year old cohort there was no significant increase in alcohol-impaired driving across the waves, and also no significant variation of the growth rate of alcohol-impaired driving across the respondents. These findings indicated that interventions focused on reducing delinquency, alcohol and drug use by sixteen and seventeen year old male adolescents will also reduce their alcohol-impaired driving.

Results Analysis of the single process model for each age cohort indicated that for the cohort that was eighteen at Wave 1, although the average rate of alcohol-impaired driving had a significant increase across the three waves, there was no significant variation across the respondents in the rate. For the age group of nineteen, the average rate of alcohol-impaired driving had no significant variation across the three waves and across the respondents. There was no need to conduct multiple-process-model analysis of these age groups to determine what factors predicted the increase and variation. In contrast, the results of single process models for both cohorts of age sixteen and seventeen showed that the average rates of alcohol-impaired driving significantly increased across the three waves (slope mean = 0.23 for the age sixteen cohort and 0.23 for the age seventeen cohort) and individual growth curves significantly varied in these rates (slope variance = 0.34 for the age sixteen cohort and 0.46 for the age seventeen cohort). Based on these results, the study further conducted multiple-process-model analyses for both age cohorts to determine whether the growth rate of delinquency significantly affected the growth rate of alcohol-impaired driving along with the control variables. The results of both single- and multiple-process-model analyses were presented in Table 3. Table 3. SEM growth curve models of delinquency and alcohol-impaired driving with alcohol-impaired driving as the endogenous variable Variable Age cohort of sixteen Age cohort of seventeen Single process model Multiple process model Single process model Multiple process model Delinquency slope ------ 0.04** ------ 0.03 (0.01) (0.06) Race (White) ------ 0.17 ------ 0.03 (0.09) (0.09) Family SES ------ -0.01 ------ 0.04 (0.03) (0.03) Drinking slope ------ 0.56** ------ 0.60** (0.18) (0.15) Drug use slope ------ 0.06 ------ 1.47* (0.08) (0.62) DWI intercept mean 0.22** ------ 0.35** ------ (0.06) (0.09) DWI slope mean 0.23** ------ 0.23** ------ (0.06) (0.07) Covariance of DWI -0.09 ------ -0.42** ------ intercept and slope (0.07) (0.12) Variance Intercept 0.31** 0.17** 0.98** 0.79** (0.10) (0.05) (0.21) (0.18) Slope 0.34** ------ 0.46** ------ (0.07) (0.10) Model fit indexes χ2 1.759 79.673 2.990 115.291* df 1 63 1 64 GFI 0.984 0.934 0.956 0.901 CFI 0.990 0.983 0.963 0.931 Notes: n = 166 for the age cohort of sixteen and 142 for the age cohort of seventeen. *p < .05 **p < .01. Table options The results of the multiple process model for the age sixteen cohort indicated that the delinquency slope significantly and positively affected the slope of alcohol-impaired-driving (b = 0.04), meaning that as the rate of delinquency was rising in this age cohort, the rate of alcohol-impaired driving was likely to increase faster. The drinking slope had a similar effect (b = .56). As the rate of drinking was increasing, the rate of alcohol-impaired driving was also likely to increase faster. In contrast, the results of the multiple process model for the age seventeen cohort showed that the delinquency slope had no effect on the slope of alcohol-impaired driving. Both drinking and drug slopes, however, had significant effects on the slope of alcohol-impaired driving (b = 0.60 for the drinking slope and 1.47 for the drug slope). As the rates of drinking and drug use were increasing in this age cohort, the rate of alcohol-impaired driving was likely to increase faster.4 In addition, the results in Table 3 showed that the average level of alcohol-impaired driving at Wave 1 was statistically significant for both age cohorts (intercept mean = 0.22 for the age sixteen cohort and 0.35 for the age seventeen cohort) and it significantly varied across the respondents in each age cohort (intercept variance = 0.31 for the age sixteen cohort and 0.98 for the age seventeen cohort). It implied significant individual variability in the initial status of alcohol-impaired driving in each of these age cohorts at Wave 1. Also, for the age sixteen cohort, there was no significant correlation between the initial status of alcohol-impaired driving at Wave 1 and the growth rate across waves. In contrast, for the age seventeen cohort, there was a significant and negative correlation between the initial status of alcohol-impaired driving at Wave 1 and the growth rate across waves (covariance = -0.42). It implied that if respondents in this age cohort had a higher level of alcohol-impaired driving at Wave 1, they were likely to have a lower growth rate of alcohol-impaired driving across the three waves.