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Do substance use risk personality dimensions predict the onset of substance use in early adolescence? A variable- and person-centered approach.

Malmberg M, Kleinjan M, Vermulst AA, Overbeek G, Monshouwer K, Lammers J, Engels RC - J Youth Adolesc (2012)

Bottom Line: For that purpose, longitudinal data of a broader effectiveness study were used from 758 early adolescents (53 % female) aged 11-14 years.Latent profile analyses on the first wave data revealed a three-profile solution for boys (i.e., resilients, internalizers, and externalizers) and a two-profile solution for girls (i.e., resilients and internalizers).In contrast to our expectation, further analyses revealed no significant differences in substance use between the different subprofiles for both boys and girls.

View Article: PubMed Central - PubMed

Affiliation: Behavioural Science Institute, Radboud University Nijmegen, P.O. Box 9104, 6500 HE, Nijmegen, The Netherlands. m.malmberg@pwo.ru.nl

ABSTRACT
Various studies found personality to be related to substance use, but little attention is paid to the role of personality risk dimensions with regard to an early onset of alcohol, tobacco, and marijuana use. Therefore, the current study used a variable-centered approach to examine whether anxiety sensitivity, hopelessness, sensation seeking, and impulsivity predict the onset of alcohol, tobacco, and marijuana use in early adolescence. Additionally, we adopted a person-centered approach to examine whether different personality subgroups could be identified, and whether these subgroups would be predictive of substance use. For that purpose, longitudinal data of a broader effectiveness study were used from 758 early adolescents (53 % female) aged 11-14 years. Structural equation models showed that hopelessness and sensation seeking were predictive of having ever used alcohol and tobacco. Also, sensation seeking was predictive of marijuana use. Latent profile analyses on the first wave data revealed a three-profile solution for boys (i.e., resilients, internalizers, and externalizers) and a two-profile solution for girls (i.e., resilients and internalizers). In contrast to our expectation, further analyses revealed no significant differences in substance use between the different subprofiles for both boys and girls. The separate personality dimensions thus seem more relevant in predicting the onset of substance use compared to the personality profiles. However, the personality profiles might be informative in explaining more excessive substance use behaviors.

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Related in: MedlinePlus

Standardized estimates of relationships between SURPS personality dimensions (T1) and substance use (20 months later) (n = 758). Note. Sex and education were specified as covariates. * p < .05, ** p < .01, *** p < .001
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Fig1: Standardized estimates of relationships between SURPS personality dimensions (T1) and substance use (20 months later) (n = 758). Note. Sex and education were specified as covariates. * p < .05, ** p < .01, *** p < .001

Mentions: Then, in our variable-centered approach, we investigated the longitudinal relationships between the SURPS personality dimensions and lifetime prevalence’s by specifying and testing a first model (see Fig. 1) with structural equation modeling (SEM) in Mplus 6.1 (Muthén and Muthén 1998–2010). In these models, we included lifetime prevalence of alcohol, tobacco, and marijuana as observed variables and we added the personality dimensions as latent constructs, with separate scale items as indicators. Sex and education were specified as covariates in the model if the preceding MANOVA’s showed significant effects. The items of the personality dimensions have response categories varying from 1 to 4 and were treated as ordered categorical variables. We estimated the parameters in the model with probit regression using the Weighted Least Square with Mean- and Variance- adjusted Chi-square test statistic (WLSMV) estimator. The Chi-square and the p value, the Comparative Fit Index (CFI: Bentler 1989), and the Root Mean Square Error of Approximation (RMSEA: Steiger 1990) were used to assess the goodness of fit of the model (Hu and Bentler 1999). We used the explained variance as a measure of effect size (Cohen 1992). To correct for the multilevel structure of our data (i.e., data of individual students are nested within schools), we used the COMPLEX procedure in Mplus (cf Kuntsche and Jordan 2006; Malmberg et al. 2010b). To handle the problem of missing values, Mplus uses all available pairwise information in the data (Full Information Maximum Likelihood (FIML): Muthén and Muthén 1998–2010).Fig. 1


Do substance use risk personality dimensions predict the onset of substance use in early adolescence? A variable- and person-centered approach.

Malmberg M, Kleinjan M, Vermulst AA, Overbeek G, Monshouwer K, Lammers J, Engels RC - J Youth Adolesc (2012)

Standardized estimates of relationships between SURPS personality dimensions (T1) and substance use (20 months later) (n = 758). Note. Sex and education were specified as covariates. * p < .05, ** p < .01, *** p < .001
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3473183&req=5

Fig1: Standardized estimates of relationships between SURPS personality dimensions (T1) and substance use (20 months later) (n = 758). Note. Sex and education were specified as covariates. * p < .05, ** p < .01, *** p < .001
Mentions: Then, in our variable-centered approach, we investigated the longitudinal relationships between the SURPS personality dimensions and lifetime prevalence’s by specifying and testing a first model (see Fig. 1) with structural equation modeling (SEM) in Mplus 6.1 (Muthén and Muthén 1998–2010). In these models, we included lifetime prevalence of alcohol, tobacco, and marijuana as observed variables and we added the personality dimensions as latent constructs, with separate scale items as indicators. Sex and education were specified as covariates in the model if the preceding MANOVA’s showed significant effects. The items of the personality dimensions have response categories varying from 1 to 4 and were treated as ordered categorical variables. We estimated the parameters in the model with probit regression using the Weighted Least Square with Mean- and Variance- adjusted Chi-square test statistic (WLSMV) estimator. The Chi-square and the p value, the Comparative Fit Index (CFI: Bentler 1989), and the Root Mean Square Error of Approximation (RMSEA: Steiger 1990) were used to assess the goodness of fit of the model (Hu and Bentler 1999). We used the explained variance as a measure of effect size (Cohen 1992). To correct for the multilevel structure of our data (i.e., data of individual students are nested within schools), we used the COMPLEX procedure in Mplus (cf Kuntsche and Jordan 2006; Malmberg et al. 2010b). To handle the problem of missing values, Mplus uses all available pairwise information in the data (Full Information Maximum Likelihood (FIML): Muthén and Muthén 1998–2010).Fig. 1

Bottom Line: For that purpose, longitudinal data of a broader effectiveness study were used from 758 early adolescents (53 % female) aged 11-14 years.Latent profile analyses on the first wave data revealed a three-profile solution for boys (i.e., resilients, internalizers, and externalizers) and a two-profile solution for girls (i.e., resilients and internalizers).In contrast to our expectation, further analyses revealed no significant differences in substance use between the different subprofiles for both boys and girls.

View Article: PubMed Central - PubMed

Affiliation: Behavioural Science Institute, Radboud University Nijmegen, P.O. Box 9104, 6500 HE, Nijmegen, The Netherlands. m.malmberg@pwo.ru.nl

ABSTRACT
Various studies found personality to be related to substance use, but little attention is paid to the role of personality risk dimensions with regard to an early onset of alcohol, tobacco, and marijuana use. Therefore, the current study used a variable-centered approach to examine whether anxiety sensitivity, hopelessness, sensation seeking, and impulsivity predict the onset of alcohol, tobacco, and marijuana use in early adolescence. Additionally, we adopted a person-centered approach to examine whether different personality subgroups could be identified, and whether these subgroups would be predictive of substance use. For that purpose, longitudinal data of a broader effectiveness study were used from 758 early adolescents (53 % female) aged 11-14 years. Structural equation models showed that hopelessness and sensation seeking were predictive of having ever used alcohol and tobacco. Also, sensation seeking was predictive of marijuana use. Latent profile analyses on the first wave data revealed a three-profile solution for boys (i.e., resilients, internalizers, and externalizers) and a two-profile solution for girls (i.e., resilients and internalizers). In contrast to our expectation, further analyses revealed no significant differences in substance use between the different subprofiles for both boys and girls. The separate personality dimensions thus seem more relevant in predicting the onset of substance use compared to the personality profiles. However, the personality profiles might be informative in explaining more excessive substance use behaviors.

Show MeSH
Related in: MedlinePlus