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Substance use risk profiles and associations with early substance
use in adolescence

Monique Malmberg • Geertjan Overbeek •

Karin Monshouwer • Jeroen Lammers •

Wilma A. M. Vollebergh • Rutger C. M. E. Engels

Received: November 9, 2009 / Accepted: June 30, 2010 / Published online: July 13, 2010

� The Author(s) 2010. This article is published with open access at Springerlink.com

Abstract We examined whether anxiety sensitivity,

hopelessness, sensation seeking, and impulsivity (i.e.,

revised version of the Substance Use Risk Profile Scale)

would be related to the lifetime prevalence and age of onset

of alcohol, tobacco, and cannabis use, and to polydrug use

in early adolescence. Baseline data of a broader effec-

tiveness study were used from 3,783 early adolescents aged

11–15 years. Structural equation models showed that

hopelessness and sensation seeking were indicative of ever-

used alcohol, tobacco or cannabis and for the use of more

than one substance. Furthermore, individuals with higher

levels of hopelessness had a higher chance of starting to

use alcohol or cannabis at an earlier age, but highly anxiety

sensitive individuals were less likely to start using alcohol

use at a younger age. Conclusively, early adolescents who

report higher levels of hopelessness and sensation seeking

seem to be at higher risk for an early onset of substance use

and poly substance use.

Keywords Alcohol use � Tobacco use � Cannabis use �
Personality � Early adolescence

Introduction

Dutch adolescents are one of the leaders in terms of

drinking frequency and binge drinking in Europe and they

usually start drinking in early adolescence (Hibell et al.

2009). Also, their use of tobacco and cannabis increases

rapidly during this period (Monshouwer et al. 2008). This

is disturbing in that early initiation of substance use has

many detrimental consequences, like distortion of brain

development (e.g., Tapert et al. 2002) and elevated risk for

later dependence and misuse (e.g., Andersen et al. 2003).

Further, early initiation increases the likelihood of poly

substance use (Ellickson et al. 2003) that, in turn, leads to

more damaging health effects (Feigelman et al. 1998).

Thus, identifying risk profiles of early adolescent girls and

boys is of crucial importance, because it may facilitate

adequate prevention efforts targeted at youths who are at

risk for an early onset of substance use or abuse (e.g.,

Conrod et al. 2008, 2010).

It is well known that personality is associated with

substance use (e.g., Flory et al. 2002) and in general, per-

sonality dimensions involving neurotic tendencies or defi-

cits in behavioral inhibition are found to best predict

substance (mis)use (e.g., Barrett et al. 1998; Cloninger

et al. 1991). Furthermore, personality dimensions con-

cerning specific, rather than general personality disposi-

tions are of most interest for substance related behaviors

(Caspi et al. 1996; Comeau et al. 2001; Jackson and Sher

2003; Woicik et al. 2009). One instrument that specifically

taps specific personality dimensions involving neurotic

tendencies and inhibition deficits is the Substance Use Risk

M. Malmberg (&) � R. C. M. E. Engels

Behavioural Science Institute, Radboud University Nijmegen,

P.O. Box 9104, 6500 HE Nijmegen, The Netherlands

e-mail: [email protected]

G. Overbeek

Developmental Psychology, Utrecht University, Utrecht,

The Netherlands

K. Monshouwer � J. Lammers

Trimbos Institute (Netherlands Institute of Mental Health

and Addiction), Utrecht, The Netherlands

K. Monshouwer � W. A. M. Vollebergh

Department of Interdisciplinary Social Science,

Utrecht University, Utrecht, The Netherlands

123

J Behav Med (2010) 33:474–485

DOI 10.1007/s10865-010-9278-4

Profile Scale (SURPS; Woicik et al. 2009). This instrument

measures four distinct and independent personality traits

(i.e., anxiety sensitivity, hopelessness, sensation seeking,

and impulsivity) that are hypothesized and actually ap-

peared to be related to high and problematic substance use

behaviors (Conrod et al. 1998; Jackson and Sher 2003;

Pulkkinen and Pitkänen 1994; Shall et al. 1992; Sher et al.

2000; Stewart et al. 1995) and other risk behaviors (e.g.,

delinquency; Woicik et al. 2009).

The first trait (i.e., anxiety sensitivity) refers to the fear

of symptoms of psychical arousal (e.g., feeling dizzy or

faint; Reis et al. 1986) and the second (i.e., hopelessness) is

identified as a risk factor for the development of depression

(Joiner 2001). Both anxiety sensitivity and hopelessness

relate to increased levels of drinking and problem drinking

(Stewart et al. 1995; Conrod et al. 1998). The third trait

(i.e., impulsivity) involves difficulties in the regulation

(controlling) of behavioral responses (Spoont 1992) and is

related to an increased risk for early alcohol and drug

(mis)use (Pulkkinen and Pitkänen 1994). Finally, the fourth

trait (i.e., sensation seeking) is characterized by the desire

for intense and novel experiences (Zuckerman 1994) and

sensation seekers have been found to drink more and to be

more at risk for heavy alcohol use (Shall et al. 1992; Sher

et al. 2000). The four SURPS’ personality traits are based

on extended personality measures (e.g., ASI; Peterson and

Reiss 1992) and show stronger associations with these

measures than with scales measuring broader dimensions

of personality (e.g., NEO-FFI; Costa and McCrae 1992).

Sensation seeking is, for instance, related to measures of

openness and extraversion, but is more strongly related to

scales measuring venturesomeness (Eysenck and Eysenck

1978; Woicik et al. 2009).

The SURPS personality traits show some overlap with

traits of temperament (TCI; Cloninger 1998). Novelty

seeking, for example, concerns the tendency to actively

respond to new stimuli and thus reflects elements of

impulsivity and sensation seeking. Further, the SURPS

personality traits are relevant for more neuropsychological

orientations. Different reinforcement processes are as-

sumed to mediate the relationship between the SURPS

personality traits and substance use in that the personality

traits are susceptible to different types of reinforcement

(e.g., Brunelle et al. 2004; Conrod et al. 1998). Individuals

with high levels of anxiety sensitivity or hopelessness are

more sensitive for the negative reinforcement processes of

substance use (i.e., the ability of substances to relieve

negative affective states). Individuals who score high on

sensation seeking and impulsivity on the other hand are

more sensitive for the positive reinforcement processes of

substance use (i.e., the positive hedonic effects of a sub-

stance).

According to Carver et al. (2009) these processes are

even more apparent in case of low serotonergic function.

It is argued that individual differences in serotonergic

function are important for personality dispositions in that

individuals with low serotonergic function are especially

susceptible for (affective) cues of the moment (Spoont

1992), like reinforcement processes. In accordance, low

serotonergic function is related to personality dispositions

as sensation seeking, impulsivity, and depression (Carver

et al. 2009). Considering the possible contribution of the

SURPS to many different fields (e.g., neuropsychology),

the fact that a more clinical orientation (i.e., the use of

more clinical instruments like the TCI) seems less obvi-

ous for early adolescents who are in the beginning stage

of substance use, and bearing in mind that specific rather

than general personality traits are most interesting, the

SURPS is a potentially important measurement for

examining the role of personality on substance use

behaviors.

Recall that the SURPS-based personality profiles are

useful in identifying individuals who are at risk for

alcohol use and alcohol-related problems in already

using samples. However, to our knowledge no previous

study examined whether these personality profiles are

indicative of an early onset of alcohol, tobacco, canna-

bis, and poly substance use. This is unfortunate, because

on the one hand early initiation is one of the strongest

identified risk factors for alcohol (De Wit et al. 2000),

tobacco (Breslau et al. 1993), and cannabis problems

(Chen et al. 2005) in later life. Further, poly substance

use in adolescence is a significant predictor of poly

substance use in adulthood (Galaif and Newcomb 1999).

On the other hand, the developmental role of personality

dispositions is important. The lower order personality

dispositions might be overruled by higher order systems

(i.e., rational or cognitive), but only if and once the

capacity for behavioral control develops (i.e., through

maturation of the pre-frontal cortex; Carver et al. 2009).

Thus, one might argue that especially early adolescents

are vulnerable for these lower order personality predis-

positions. To conclude, focusing on early onset of sub-

stance use in early adolescence, and identifying the

specific personality profiles related to these risk behav-

iors, might help us to identify youngsters at an early age

who are at risk for developing future substance misuse

patterns.

The present study examines a SURPS-based, four-factor

personality model in relation to early onset substance use

and poly substance use. A total of 3,783 adolescents in the

ages of 11–15 participated in the first wave of the ongoing

Healthy School and Drugs (HSD) effectiveness study in

which they filled out a digital questionnaire. Participants

J Behav Med (2010) 33:474–485 475

123

answered questions about alcohol, tobacco, and cannabis

use and their personality traits. Based on previous

research on personality, we expected to find strongest

associations with substance use for sensation seeking.

Specifically, we hypothesize sensation seekers to have an

increased risk for an early initiation of alcohol, tobacco,

and cannabis use. Hence, we expected to find that anxiety

sensitive adolescents have an increased risk for an early

onset of alcohol use, adolescents reporting higher levels

of hopelessness to have an increased risk for an early

onset of alcohol and tobacco use, and impulsive adoles-

cents to have an increased risk for an early onset of

alcohol and cannabis use. Following these expectations

we also expected to find associations between the SURPS

personality profiles and poly substance use. However,

considering the lack of knowledge so far in adolescence,

no concrete expectations were formulated on poly sub-

stance use.

Method

Sample and procedure

The cross-sectional data for this study were collected as

part of a broader effectiveness study on a national school

prevention program ‘‘The Healthy school and drugs.’’ A

total of 23 schools were included from seven regions in

The Netherlands. We visited participating schools and

during these visits we provided further information about

the research project. In collaboration with the schools’

headmasters, we informed the students’ parents about the

goals of the study by a letter in which parents were also

explained they could refuse participation of their child in

the study. Approval for the design and data collection

procedures was obtained from the ethic committee of the

Radboud University Nijmegen. All data were collected

between January and March 2009. All first grade students

independently filled out a digital questionnaire during

school hours in the presence of a teacher and a research

assistant. The questionnaires were counterbalanced on

alcohol, tobacco, and cannabis, thus six different versions

were administrated.

In total, 3,783 first-grade students took part in the study

of whom 231 (6.1%) were absent (i.e., illness) during data-

collection and three participants were declined participa-

tion by their parents. The total sample included 1,856 boys

(49.1%) and 31.5% (n = 1,192) of all participants pursued

lower secondary vocational education, 46.6% (n = 1,764)

pursued pre-university education, and 21.9% (n = 827) of

the students pursued a mixed educational program. Of the

participants who completed the questionnaire 3,375 par-

ticipants (96.2%) were of Dutch ethnic origin. Students

ranged in age from 11 to 15 years (M = 13.01, SD = .49).

For the question on lifetime prevalence of alcohol use,

2,103 (59.9%) reported to have at least once used alcohol

in the past. With regard to smoking, 768 (22.1%) partici-

pants had ever smoked, and with regard to cannabis 75

(2.1%) participants reported to have at least once used

cannabis. Finally, 670 (19.6%) stated that they already had

tried more than one substance.

Measures

Personality profiles

The Substance Use Risk Profile Scale (SURPS; Woicik

et al. 2009) distinguishes four personality dimensions,

namely anxiety sensitivity, hopelessness, sensation seek-

ing, and impulsivity. Each dimension was assessed using

five to seven items that could be answered on a 4-point

scale, ranging from 1 = ‘strongly agree’ to 4 = ‘strongly

disagree.’ Anxiety sensitivity refers to the fear for physical

arousal and an example item is: ‘It’s frightening to feel

dizzy or faint.’ Hopelessness concerns negative thinking

which might lead to depression proneness and ‘I feel that

I’m a failure’ is an example item. Sensation seeking is

characterized by wanting to try out new things and an

example of such an item is ‘I like doing things that frighten

me a little.’ Finally impulsivity refers to having difficulties

in controlling behavioral responses, and ‘I usually act

without stopping to think’ is an example item. Factor

structure, internal consistency and test–retest reliability, as

well as construct, convergent, and discriminant validity of

this instrument were shown to be adequate in studies

among college students and adult samples (e.g., Krank

et al. submitted). Because the instrument was translated in

Dutch and used for the first time the factor structure was

examined using Exploratory Factor Analysis (EFA) on a

randomly selected sample that consisted of the first half of

the original sample using Mplus (Muthén and Muthén

1998–2007). The Weighted Least Square parameter esti-

mator with Mean- and Variance adjusted chi-square test

statistic (WLSMV) was used because the metric of the

items is more ordered categorical than interval level. The

sample was randomly divided into two subsamples. Two

items were removed. The first item (i.e., I feel that I’m a

failure) had substantial loadings (.38 and .42, respectively)

on the factors anxiety sensitivity and hopelessness. The

second item (i.e., I feel I have to be manipulative to get

what I want) showed an almost zero loading on the factor

impulsiveness. A Confirmatory Factor Analysis (CFA) was

performed on the remaining 21 SURPS items on the other

half of the sample and confirmed the four-factor structure

of the SURPS. The final model had a satisfactory fit to

the data (v2 (54) = 611.315, P .001, RMSEA = .055,

476 J Behav Med (2010) 33:474–485

123

CFI = .943). Cronbach’s alphas were .69 for anxiety

sensitivity (factor loadings between .42 and .72), .85 for

hopelessness (loadings between .72 and .96), .68 for sen-

sation seeking (loadings between .38 and .72), and .67

for impulsivity (loadings between .48 and .72). These

reliability estimates converge with those from previous

research (e.g., Jaffee and D’Zurilla 2009) and are satis-

factory for short scales (Loewenthal 1996).

Substance use

We assessed adolescents’ alcohol use in terms of lifetime

prevalence, or whether participants had ever consumed

alcohol in their life. Lifetime prevalence was measured by

asking: ‘‘Have you ever drunk alcohol?’’ Participants could

answer this question with yes (=1) or no (=0). To determine

the age of onset of participants’ alcohol use we asked how

old they were when they had first drunk alcohol (Kuntsche

et al. 2009).

Lifetime prevalence of tobacco use was measured by a

single item on a 9-point scale ranging from 1 = ‘I never

smoked, not even a puff’ to 9 = ‘I smoke at least once a

day’ (Kremers et al. 2001). To tap lifetime prevalence of

smoking, adolescents who responded in the categories 2–9

were categorized as tried smoking before (=1), and the

adolescents who responded in category 1 were categorized

as never tried smoking (=0) following Kremers (2002). In

order to assess age of onset, participants who had ever

smoked were asked how old they were when they smoked

their first puff.

We assessed the lifetime prevalence of cannabis use

through a single item, namely: ‘‘Have you ever used can-

nabis?’’ (Monshouwer et al. 2005). Participants could an-

swer with yes (=1) or no (=0). Subsequently, participants

who ever used cannabis were asked how old they were

when they first used cannabis.

Finally, poly substance use was operationalized by the

use of more than one substance, regardless of the combi-

nation or amount of substances used. A new variable was

created in which all adolescents who used more than

one substance were categorized as poly substance users

(=1) and all other adolescents as non-poly substance users

(=0).

Strategy of analyses

First, descriptive analyses and Pearson correlations of age

of onset of alcohol, tobacco, and cannabis use and the

personality profiles (i.e., anxiety sensitivity, hopelessness,

sensation seeking, and impulsivity) were calculated

between model variables. Second, to investigate whether

participants’ sex and educational level should be specified

as covariates in the model, a MANOVA was conducted to

compare responses on the SURPS personality profiles be-

tween males and females and between different educational

levels. Another MANOVA was carried out to investigate

sex and educational differences on substance use. Also,

separate ANOVA’s were conducted to examine sex and

educational level differences on age of onset of alcohol,

tobacco, and cannabis use. The effect sizes (i.e., partial eta

squared) are reported for the analyses of variance. With

respect to the effect size, values around .02 are considered

small effects, values around .15 medium effects, and values

around .35 large effects (Cohen 1992). Post-hoc tests with

Bonferroni corrections were carried out to investigate the

significant differences in educational level on the outcome

variables.

Next, to investigate the relationships between person-

ality profiles and lifetime prevalence of alcohol, tobacco,

and cannabis use, we specified and tested a first model

(see Fig. 1) with structural equation modeling (SEM) in

Mplus (Muthén and Muthén 1998–2007). In this model,

lifetime prevalences of alcohol, tobacco, and cannabis

were included as observed variables and personality

profiles were added as latent constructs, with separate

scale items as indicators. Sex and educational level were

specified as covariates in the model. We used the

weighted least square method (WLSMV) to estimate

parameters in the model. The Chi-square and the p-value,

the Comparative Fit Index (CFI: Bentler 1989), and the

Anxiety
Sensitivity

Hopeless-
ness

Sensation
Seeking

Alcohol
use

Tobacco
use

Cannabis
use

8

10

21

18

14

6

3

23

20

13

7

4

1

19

12

9

.43

-.08*

.65

.73

.68

.57

.73

.73

.85

.73

.96

.77

.55

.60

.71

.54

.66

Impulsivity

15

5

2

11

.48

.59

.73

.57

.16

-.01

-.05

-.04
-.09

.30*

.42***

.43***

.31***

.36***

.21**

16 .36

Fig. 1 Standardized estimates of associations between SURPS

personality profiles and lifetime prevalence of substance use

(n = 3,783). * P .05, ** P .01, *** P .001

J Behav Med (2010) 33:474–485 477

123

Root Mean Square Error of Approximation (RMSEA:

Steiger 1990) were used to assess the goodness of fit of

the model. With respect to the CFI, values above .90

indicate an acceptable fit and values above .95 signify an

excellent fit to the data. Concerning the RMSEA, values

below .08 point to an acceptable fit and values below .05

indicate a good fit of the model to the data (Hu and

Bentler 1999). The explained variance was used as a

measure of effect size. Values around 2% are considered

small, values around 15% medium, and values around

35% are considered large effects (Cohen 1992). The data

have a multilevel structure (i.e., data of individual stu-

dents are nested within classes), which means that apart

from differences between individuals, average substance

use levels across classes may vary as well. In particular,

participants within certain classes may be more similar

to each other due to specific influence and selection

processes (Kuntsche et al. 2008); classmates in our tar-

get group might influence each other in such a way that

their substance using behaviors become more similar.

This means that individual respondents are not inde-

pendent within classes. As a consequence the standard

errors of the parameter estimates are biased leading to

incorrect decisions about the significance of parameter

estimates. The COMPLEX procedure in Mplus is used

to correct for dependency of the data, which results

in unbiased standard errors (cf Kuntsche and Jordan

2006).

To investigate the relationship between personality

profiles and age of onset of alcohol, tobacco, and can-

nabis use only substance users were included in the

subsequent analyses (e.g., only those who already drank

alcohol were included in the analysis to see whether

personality profiles were related to the age of onset of

alcohol use). The personality profiles were again included

in the model as latent constructs and the age of onset as

an observed variable. Identical statistical procedures were

used as in the former model. Finally, to investigate the

relationship between personality profiles and poly sub-

stance use two variables were created in the dataset, one

for mono use and one for poly use. All participants that

only used one substance were assigned a score ‘1’ and all

others were assigned ‘0’ in the mono variable. For poly

substance use, all participants who reported having used

two or three substances were assigned ‘1’ and all others

were assigned ‘0’. Based on this information, we esti-

mated the two models with the same procedures as the

other models in Mplus.

Results

Descriptive analyses

Table 1 presents the means and standard deviations of the

SURPS’ personality profiles and age of onset examined in

the present study, separately for educational level and sex.

For Pearson correlations of the model variables we refer to

‘‘Appendix’’. A MANOVA was conducted to examine

whether personality profiles would significantly differ

across sex and educational level. Main effects of sex [F(4,

3,431) = 86.40, P .001, gp
2 = .092] and education [F(8,

6,862) = 15.92, P .001, gp
2 = .018] emerged in the

MANOVA on different personality profiles. Univariate

tests showed sex effects for anxiety sensitivity [F(1,

3,434) = 110.79, P .001, gp
2 = .031], hopelessness [F(1,

3,434) = 5.50, P = .02, gp
2 = .002], and sensation seeking

[F(1, 3,434) = 212.69, P .001, gp
2 = .058]. Specifically,

we found that girls reported higher scores on anxiety sen-

sitivity and hopelessness than boys, and boys reported

higher levels of sensation seeking than girls. Associa-

tions were also found between education and hopelessness

Table 1 Means and standard deviations for personality profiles and age of onset

Gender Educational level Total

Female Male Lower Mixed Higher

Age of onset

Alcohol 10.40 (2.19)* 9.67 (2.50)* 10.41 (2.44)ab 9.93 (2.40)a 9.77 (2.30)b 10.01 (2.38)

Tobacco 11.26 (1.67)* 10.91 (1.99)* 11.31 (1.79)ab 10.90 (2.01)a 10.81 (1.81)b 11.07 (1.86)

Cannabis 12.45 (.74) 11.90 (1.53) 12.28 (1.08) 11.75 (1.24) 11.75 (2.18) 12.07 (1.36)

Personality profiles

Anxiety sensitivity 2.38 (.62)* 2.13 (.67)* 2.30 (.72)a 2.27 (.66) 2.23 (.62)a 2.26 (.66)

Hopelessness 1.55 (.53)* 1.50 (.56)* 1.64 (.63)ab 1.51 (.51)a 1.46 (.49)b 1.52 (.55)

Sensation seeking 2.38 (.66)* 2.72 (.66)* 2.49 (.70)ab 2.60 (.69)a 2.56 (.67)b 2.55 (.68)

Impulsivity 2.18 (.59) 2.23 (.64) 2.29 (.66)a 2.24 (.61)b 2.14 (.58)ab 2.21 (.62)

Means with the same superscripts are significantly different from each other. All at P .05 with Bonferroni corrections for educational level

478 J Behav Med (2010) 33:474–485

123

[F(2, 3,434) = 36.40, P .001, gp
2 = .021], sensation seeking

[F(2, 3,434) = 9.73, P .001, gp
2 = .006], and impulsiv-

ity [F(2, 3,434) = 21.88, P .001, gp
2 = .013]. Students

of higher education reported higher scores on impulsivity

and hopelessness compared to students of lower educa-

tion. The pattern for sensation seeking was somewhat

different. Students of mixed education reported higher

scores than students in both lower and higher educational

levels, but students of higher education scored higher than

students of lower education.

Another MANOVA was conducted to look at possible

differences for sex and educational level on substance use.

We found main effects for both sex [F(4, 3,411) = 11.04,

P .001, gp
2 = .013] and education [F(8, 6,822) = 23.80,

P .001, gp
2 = .027] on substance use. Univariate tests

showed sex effects for alcohol [F(1, 3,414) = 23.98, P
.001, gp

2 = .007], tobacco [F(1, 3,414) = 17.72, P
.001, gp

2 = .005], cannabis [F(1, 3,414) = 17.51, P .001,

gp
2 = .005], and poly substance use [F(1, 3,414) = 17.75,

P .001, gp
2 = .005]. Particularly, we found that more

boys already used the different substances compared to

girls and more boys were poly substance users in contrast

to girls. Univariate tests also showed education effects

on alcohol [F(2, 3,414) = 3.32, P = .04, gp
2 = .002],

tobacco [F(2, 3,414) = 88.89, P .001, gp
2 = .049], can-

nabis [F(2, 3,414) = 17.96, P .001, gp
2 = .010] and poly

substance use [F(2, 3,414) = 70.68, P .001, gp
2 = .040].

More students of lower education reported having used

alcohol, tobacco, or cannabis compared to students from

higher education. Also, students of lower education were

more likely to use more than one substance compared with

students from higher education.

We conducted a set of three ANOVA’s to test sex and

education differences for age of onset of alcohol use, tobacco

use, and cannabis use. Main effects of sex [F(1, 2,038) =

51.07, P .001, gp
2 = .024] and education [F(2, 2,038) =

14.05, P .001, gp
2 = .014] were found for the age of onset

of alcohol. With regard to tobacco use we found main effects

of sex [F(1, 745) = 5.65, P = .02, gp
2 = .008] and educa-

tion [F(2, 745) = 5.20, P .01, gp
2 = .014]. Finally, the

last ANOVA in which age of onset of cannabis use

was the dependent variable, showed no main effects

for sex and education. In sum, the results indicated

that boys and students from higher education start drinking

and smoking earlier compared to girls and students

from lower education. Overall, although the effects

of sex and educational level on substance use and person-

ality were small, they were still significant and

were therefore specified as covariates in the subsequent

analyses.

Personality profiles and lifetime prevalence

The model as depicted in Fig. 1 showed a good fit to

the data [v2 (df = 68, n = 3,783) = 725.791, P .001,

RMSEA = .051, CFI = .929]. As can be seen in Fig. 1,

standardized estimates for the associations between per-

sonality profiles and lifetime prevalences revealed signifi-

cant associations between anxiety sensitivity (b = -.08,

P = .024), hopelessness (b = .31, P .001), and sensa-

tion seeking (b = .43, P .001) with the lifetime preva-

lence of alcohol use. These results indicate that youngsters

with lower levels of anxiety sensitivity and higher levels of

hopelessness and sensation seeking were more likely to

have ever consumed alcohol. Further, we found signifi-

cant associations between hopelessness (b = .36,

P .001) and sensation seeking (b = .42, P .001) with

the lifetime prevalence of tobacco use. Adolescents who

were high on hopelessness and sensation seeking were

more likely to have ever smoked than adolescents who

were low on these two profiles. Finally, the analysis

showed significant linkages between hopelessness

(b = .21, P = .007), sensation seeking (b = .30, P =

.023) and lifetime prevalence of cannabis use. This means

that youngsters who had higher levels of hopelessness and

sensation seeking had a higher chance of having ever used

cannabis at this age than youngsters who had lower scores

on these profiles. The models showed medium to large

effect sizes for the relationships between the four per-

sonality profiles and substance use; they explained 19.1%

of the variance in lifetime prevalence of alcohol use,

31.3% of the variance in tobacco use, and 28.8% of the

variance in cannabis use.

Personality profiles and age of onset

The model that specified the relationship between person-

ality profiles and the age of onset of alcohol use showed

an adequate fit to the data [v2 (df = 62, n = 2,103) =

416.739, P .001, RMSEA = .052, CFI = .943]. Con-

trolling for participants’ sex and education, we found sig-

nificant associations between hopelessness and age of onset

of alcohol use (Table 2). This result showed that students

start to drink at a younger age when they have higher levels

of hopelessness. The model that assessed the relationship

between personality profiles and age of onset of tobacco

use also showed an adequate fit to the data [v2 (df = 58,

n = 768) = 228.326, P .001, RMSEA = .062, CFI =

.928]. Table 2 shows the standardized estimates of this

model; we did not find any significant associations between

the personality profiles and the age of onset of tobacco use.

J Behav Med (2010) 33:474–485 479

123

We could not adequately test the relationship between

personality profiles and age of onset of cannabis use con-

sidering the small sample size of cannabis users (n = 75).

As an alternative (to reduce the number of parameters to

be estimated) we applied regression analysis in Mplus

with sex and education as control variables and the four

manifest personality profiles as predictors of age of onset

of cannabis use. We found a significant relationship

between hopelessness and age of onset of cannabis

use (b = -.37, P = .001) indicating that an increase of

hopelessness is associated with a decrease of age of onset

of cannabis use. The models showed small effect sizes for

the association between the four personality profiles—

controlling for sex and educational level—and the age of

onset of alcohol (R2 = 5%) and tobacco (R2 = 3.3%) use,

and a medium effect size for the relationship between

personality profiles, sex and educational level on the one

hand and the age of onset of cannabis use on the other

(R2 = 17.7%).

Personality profiles and poly substance use

The mono substance use model showed a good fit to

the data [v2 (df = 62, n = 3,783) = 656.514, P .001,

RMSEA = .050, CFI = .937]. Significant associations

were found between hopelessness and sensation seeking

with mono substance use (Table 2). Thus, students that

experienced more feelings of hopelessness or students who

were higher on sensation seeking were also more likely

to use one specific substance (i.e., either alcohol, tobacco,

or cannabis). The model examining poly substance use

showed a good fit to the data [v2 (df = 62, n = 3,783) =

693.229, P .001, RMSEA = .052, CFI = .933]. The

results in Table 2 display significant associations between

hopelessness, sensation seeking, and poly substance use.

Thus, more feelings of hopelessness and being a sensation

seeker were related to the use of more than one substance.

The model on mono-substance use showed a medium

effect size (R2 = 11.4%) for the four personality profiles

and the model on poly substance use a large effect size

(R2 = 31.8%).

Discussion

The results clearly demonstrated that, overall, three out of

the four SURPS’ personality profiles are associated with

early adolescents’ substance use behavior. Notably, the

different models revealed that—in this sample of early

adolescents, of whom many are in the starting phase of

experimentation with substance use—especially hope-

lessness and sensation seeking are strongly associated

with a higher chance of ever-used alcohol, tobacco, and

cannabis at an early age and with poly substance use.

Individuals with higher levels of hopelessness have also a

higher chance of starting to use alcohol or cannabis at an

earlier age. Highly anxiety sensitive individuals on the

other hand are less likely to start using alcohol use at a

younger age.

Personality profiles and lifetime prevalence

Previous studies investigating the role of the SURPS

personality profiles on alcohol use mainly focused on

more advanced levels of drinking (e.g., Cooper et al.

1995). Our present results extend this knowledge by

demonstrating that the revised SURPS personality profiles

are not only indicative of already established maladaptive

drinking patterns in adolescents and adults (e.g., Sher

et al. 2000), but are also associated with alcohol use in

young adolescents. Specifically, the SURPS personality

profiles are associated with early adolescents’ alcohol use

to a moderately strong degree. For this particular age

group, we found that especially hopelessness and sensa-

tion seeking are indicative of having ever used alcohol in

early adolescence. The results with regard to sensation

seeking are not unexpected given the novelty seeking

nature of sensation seekers and that experimenting with

Table 2 Standardized estimates and standard errors for tested models

Age of onset Substance use

Alcohol Tobacco Cannabis Mono Poly

b SE b SE b SE b SE b SE

Anxiety .01 .03 .03 .06 .01 .11 -.04 .04 -.07 .04

Hopelessness -.10** .04 -.04 .05 -.37** .17 .22*** .04 .37*** .04

Sensation -.06 .05 .11 .09 -.22 .10 .34*** .06 .43*** .06

Impulsivity -.05 .05 -.09 .08 -.02 .10 -.05 .07 .01 .07

** P .01, *** P .001

480 J Behav Med (2010) 33:474–485

123

different substances can be seen as such novel experi-

ences. Although it was not clear what the role of hope-

lessness would be in our age group, we did find it

surprising that hopelessness seems this important in our

age group, since this trait was primarily found to be

predictive of a progression into substance misuse before

(e.g., Jackson and Sher 2003). One possible explanation is

that hopelessness leads adolescents to initiate substance

use as a means to cope with negative thoughts. Therefore,

we examined if higher scores on different coping strate-

gies (e.g., drinking alcohol makes me relaxed) were re-

lated to higher levels of hopelessness. However, we could

not substantiate this explanation based on these additional

analyses of our data. More information on these analyses

can be obtained from the first author.

Another explanation is that early childhood problems

(e.g., family violence, unorganized family environments,

antisocial behavior) can lead to both negative affect (e.g.,

Reinherz et al. 2003) and an early onset of substance use

(e.g., Dishion et al. 1999). The existing relationship be-

tween hopelessness and the lifetime prevalences might

then be based on a third variable explanation, indicating

that early childhood adversity can affect the development

of personality profiles, and subsequent engagement in

problem behaviors (Akse et al. 2004; Hale et al. 2008).

Since hopelessness is associated with self-harm and sui-

cide behavior (O’Connor et al. 2008), there might also be

a link between hopelessness and more ‘nihilistic’ behav-

iors. Further research is necessary to disentangle the po-

tential pathways in which hopelessness is related to early

substance use behaviors. Contradictive to our expectations

we found a negative association between anxiety sensi-

tivity and alcohol use. This can be explained by the

preventive effect that the fear for physical arousal might

have. When highly anxiety sensitive individuals have no

prior experience with alcohol they also do not know if

drinking alcohol leads to unusual body sensations, which

might keep them from drinking. Also, it could be that

highly anxiety sensitive individuals are more anxious in

general, and are for instance afraid of loosing control

when drinking.

Our findings also indicate a clear linkage between two

personality profiles (i.e., hopelessness and sensation seek-

ing) and ever-used tobacco in early adolescence. The few

studies that investigated the role of personality (i.e., Big

Five) on lifetime smoking in adolescence (Harakeh et al.

2006; Otten et al. 2008) found extraversion and openness to

be risk factors for lifetime smoking and conscientiousness,

agreeableness, and emotional stability to be protective

factors. Our results are in line with these latter findings,

considering that extraversion and openness are more

strongly related to sensation seeking and hopelessness is at

the opposite end of emotional stability. Finally, our results

show that sensation seeking is associated with an early

onset of cannabis use. This is in line with previous results

showing that sensation seeking predicts reckless behavior,

like cannabis use (Arnett 1994). It is thought that sensation

seekers use substances for the euphoric/intoxicating effects

(Comeau et al. 2001), so it might be that especially sen-

sation seekers attribute such characteristics to different

substances (e.g., cannabis) and are therefore more likely to

initiate use of a certain substance. We also found an

association between hopelessness and having ever used

cannabis in early adolescence. It is again not quite clear yet

how to interpret this finding in our age group. Previous

results in older adolescents suggest that hopelessness also

predicts reckless behavior, but particularly with regard to

the use of cocaine and other illegal drugs, not cannabis

(Woicik et al. 2009). Also, for this finding it might be that

early childhood problems directly affected both hopeless-

ness and the use of cannabis. Overall, the fact that the

SURPS personality profiles are related to early adolescents’

tobacco and cannabis use to a moderately strong degree

indicate that these profiles are important in explaining

individual differences in early adolescent substance use

behaviors.

Personality profiles and age of onset

We only found support for the role of hopelessness on the

age of onset of alcohol and cannabis use. We believe that

these findings might also be explained by the third vari-

able (i.e., early childhood problems) explanation. Besides

the findings considering hopelessness we hardly found

any support for the relationship between the personality

profiles and the age of onset of the different substances. It

could be that this outcome is due to the retrospective

character of these questions or to the restriction of range.

Adolescents were asked the age when they had their first

experience with a specific substance. In The Netherlands,

most adolescents start experimenting first with alcohol,

followed by tobacco and cannabis (Monshouwer et al.

2008). So, especially with respect to alcohol and tobacco

use, the recollection time between the first experience and

the moment of questioning is longer, and might thus be

less adequate (Bailey et al. 1992; Engels et al. 1997).

Simultaneously, this trend causes differences in the

diversity of answers. Since youngsters start using canna-

bis at a later age, less variation is visible in the ages of

onset compared to the start of using alcohol or tobacco.

These effects could explain the lack of findings on age of

onset of cannabis use and might explain the small effects

found for the associations between the SURPS personality

profiles and age of onset.

J Behav Med (2010) 33:474–485 481

123

Personality profiles and poly substance use

In the present study, we found that the SURPS personality

profiles are strongly related to early adolescents’ poly

substance use. Specifically, we found that hopelessness

and sensation seeking are indicative of poly substance use

and these results are mostly in line with earlier findings.

Previous studies suggested that poly substance users have

particularly high levels of impulsivity and sensation

seeking (e.g., Galizio and Stein 1983; Lacey and Evans

1986). Also, there is evidence suggesting that poly sub-

stance users are low on agreeableness and conscien-

tiousness and high on neuroticism (McCormick et al.

1998). Many of these studies examined the relationship

between personality and poly substance use in a clinical

(i.e., substance dependent) sample and as far as we know

little is known about the early onset of poly substance use

in young adolescents. In contrast to these findings,

although we found a strong link for hopelessness and

sensation seeking with poly substance use, we did not find

a relationship between impulsivity and poly substance

use. In the present study we defined poly substance use by

the use of more than one substance, comprising alcohol,

tobacco, and/or cannabis use. Other studies among older

or clinical samples usually operationalized poly substance

use by the use of multiple (hard) drugs, like cocaine, xtc,

and opiates (e.g., Smit et al. 2002). So, it might be that

impulsivity only has sufficient dicriminant power in poly

substance use, when the use of certain substances is

deviant enough.

Strengths, limitations, and implications for future

research

A major strength of our study is the large representative

non-clinical sample of our study. In addition, instead of

exclusively examining adolescents’ alcohol use we also

focused on tobacco and cannabis use. The large sample

allowed us to perform sophisticated SEM analyses in

which we controlled for the multilevel structure of the

data. Finally, a strength of the study is that our mea-

surements were well-validated and had all good psycho-

metric properties.

Some limitations were present in the current study as

well. First of all, a cross-sectional design was used—thus,

no causal explanations can be based on these associations.

Roberts et al. (2006) found in their meta-analysis that the

mean level of personality traits changed across the life

course, especially during adolescence. In general, it is

found that one’s personality type is only moderately stable

in childhood (e.g., Hart et al. 2003) and adolescence (e.g.,

Akse et al. 2007). So, do personality profiles precede

substance use behaviors or do experiences with substance

use modify personality profiles? We investigated the role

of personality in substance use in a group of early ado-

lescents that is in their initiation phase of alcohol and to-

bacco use and has hardly any experience with cannabis.

One might thus question if the potential changes in per-

sonality due to substance (ab)use are already noticeable in

these early adolescents. It seems more likely that these

changes will become apparent in a later stage, when ado-

lescents have more experience with substance use or when

more time has gone by after the actual initiation of sub-

stance use. It seems plausible to assume that, in a group of

early adolescents who are in their starting phase of sub-

stance use, personality precedes substance use behaviors.

However, this assumption should be interpreted carefully,

since longitudinal research is required to shed more light

on this topic.

Secondly, the fit of the models expressed in RMSEA

varied between .050 and .062, the CFI varied between .928

and .943. This means that the fit of the models were

acceptable but not excellent. There is ample literature

about fit indices and cut-off scores. In our view, an

important reason for the absence of excellent fit is related

to the measurement part of the models (the factor model).

In the factor model a simple structure is required with

cross-loadings constrained to be zero. In exploratory factor

models cross loadings are admitted resulting in better fit-

ting models. We applied a newly developed exploratory

structural equation model (ESEM) on the models in this

article. In these models the measurement part of the

structural model is estimated by the exploratory factor

model (Asparouhov and Muthén 2009). In fact, the con-

firmatory factor model in the structural model was replaced

by an exploratory factor model. The fit of all models were

improved with CFI-values [ .95 and RMSEA-val-

ues .05. Because the structural parameters did not

change substantially we preferred to use the classical SEM

model with the confirmatory factor model as measurement

model.

Thirdly, our use of self-reports might have lead to

measurement errors. Two perspectives can explain possible

measurement errors in self-reports on substance use,

namely a situational and a cognitive perspective (Brener

et al. 2003). The situational perspective concerns the

influence of the social environment, which might lead

adolescents to give socially desirable answers. To avoid

social desirability and optimize measurement validity we

guaranteed full confidentiality (anonymity) to our partici-

pants (e.g., Dolcini et al. 1996). The cognitive perspective

concerns the cognitive or internal processes that might

influence the self-reports. They might over or underesti-

mate their substance use behaviors in that they can not

482 J Behav Med (2010) 33:474–485

123

exactly recall what they have been using in a certain period

(e.g., Engels et al. 1997). In our study we asked participants

if they ever tried a specific substance, which is arguably

different from asking them how much they have used in a

certain period. One might expect participants to reliably

recall ever using alcohol, tobacco, or cannabis before. With

respect to the questions on age of onset the cognitive aspect

seems more relevant, thus one might argue that more

measurement errors occurred in these self-reports. How-

ever, the time between the age of first drink and assessment

seems to matter. The longer the time interval the more

severe recall bias one might expect (e.g., Engels et al.

1997; Parra et al. 2003). In our study, we investigated the

age of onset in a group of early adolescents with an average

age of 13 and assessing the reported age of onset close to

the actual age will optimize the reliability of the self-re-

ports (Kuntsche et al. 2009).

Fourthly, we only focused on the relationship between

the SURPS personality profiles and substance use behav-

iors. It would be interesting to investigate if the SURPS

personality profiles are also indicative of other risk type

behaviors. Finally, in our design we used a variable-cen-

tered approach utilizing the SURPS’ personality profiles to

examine individual differences on substance use for each

of the four profiles. However, it is also possible to inves-

tigate how constellations of traits within individuals are

organized, using a person-oriented approach (Bergman and

Magnusson 1997). The use of this approach might shed

more light on how these constellations are associated with

substance use in adolescents.

In sum, the present results suggest that in a large

sample of early Dutch adolescents especially sensation

seeking and hopelessness are strongly linked to the life-

time prevalence and age of onset of alcohol, tobacco, and

cannabis use in early adolescents. Also, hopelessness and

sensation seeking are found to be indicative of poly

substance use. Building on these new insights, it will be

crucial to conduct prospective analyses in the future to get

more insight into how personality profiles can predict the

development of substance use behaviors in adolescence

and, vice versa, to determine whether substance use may

affect adolescents’ personality development. Further, re-

cent studies investigated the effects of tailor-made inter-

ventions for the at-risk personality populations (Conrod

et al. 2006, 2008, 2010). These studies show much

promise for prevention efforts on excessive substance use,

thus it seems that knowing who is at risk and what this

risk is all about (i.e., only a risk for excessive use or also

for early initiation) in combination with such effective

prevention efforts might lead to an effective approach in

diminishing (the negative effects of) substance use among

(early) adolescents.

Acknowledgments This research was supported by a grant from

The Dutch Ministry of Health, Welfare, and Sport.

Open Access This article is distributed under the terms of the

Creative Commons Attribution Noncommercial License which per-

mits any noncommercial use, distribution, and reproduction in any

medium, provided the original author(s) and source are credited.

Appendix

See Table 3.

Table 3 Pearson correlations of personality profiles, substance use, age of onset, and poly substance use

1 2 3 4 5 6 7 8 9 10

1. Anxiety sensitivity –

2. Hopelessness -.01 –

3. Sensation seeking .02 -.15** –

4. Impulsivity .24** .08** .37** –

5. Lifetime alcohol .05** -.13** -.20** -.14** –

6. Lifetime tobacco .01 -.19** -.18** -.18** .29** –

7. Lifetime cannabis -.01 -.06** -.10** -.10** .09** .23** –

8. Age of onset alcohol .03 -.06** -.08** -.06* – .04 .02 –

9. Age of onset tobacco .03 -.08* .03 .01 .05 – .01 .38** –

10. Age of onset cannabis .05 -.25* -.19 -.01 .17 .05 – .23 .31* –

11. Poly substance use -.04* .19** .24** .20** -.84** -.77** -.23** -.04 -.04 -.12

* P .05, ** P .01

J Behav Med (2010) 33:474–485 483

123

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Instructions: Students will research an article based on a specific population. The article must come from a professional journal, and or text. Students are to identify the research methods used (example: quantitative or qualitative, etc.) and discuss the research findings. Please explain how the research evidence can improve the practice setting specific to state and local policy and service delivery. Include the author’s intent for the study and how it can inform scientific research.
Please utilize the following rubric to guide you through this assignment. (50 points)

Criteria

0

Non-Performance

8.77

Partial

9.88

Proficient

11.11

Exceptional

Required Length and typed (2.5 pages at 12.5 font)

Less than 2 pages and not typed

2 pages and typed

2.25 pages and typed

2.5 pages and typed

Student utilizes subheadings for each area to be addressed

Student failed to utilize subheadings for each area to be addressed

Student partially utilized subheadings for each area to be addressed

Student was proficient in utilizing subheadings for each area to be addressed

Student was exceptional in utilizing subheadings for each area to be addressed

Student provide a reference source for the article

Student failed to provide a reference source for the article

Student partially provided a reference source for the article

Student was proficient in providing a reference source for the article

The student was Exceptional in providing a reference source for the article

Student discuss the relevance of the article to the selected population

Student failed to discuss the relevance of the article to the selected population

Student partially discuss the relevance of the article to the selected population

Student was proficient in discussing the relevance of the article to the selected population

Student was proficient in discussing the relevance of the article to the selected population

Student discuss findings and position of the author(s) that includes the author’s intent for the study and how it can inform scientific research

Competency: 4: a

Student failed to discuss findings and position of the author(s) that includes the author’s intent for the study and how it can inform scientific research

Student partially discussed the findings and position of the author(s) that includes the author’s intent for the study and how it can inform scientific research

The student was proficient in discussing the findings and position of the author(s) that includes the author’s intent for the study and how it can inform scientific research

Student was exceptional in discussing the findings and position of the author(s) that includes the author’s intent for the study and how it can inform scientific research

Student discuss the relevance of article to the course

Student failed to discuss the relevance of the article to the course

Student partially discuss the relevance of the article to the course

Student was proficient in discussing the relevance of the article to the course

Student was exceptional in discussing the relevance of the article to the course

Student discuss the implications of article for social work practice specific to how the research evidence can improve the practice setting for state and local policy and service delivery

Competency: 4: c

Student failed to discuss the implications of the article for social work practice specific to how the research evidence can improve the practice setting for state and local policy and service delivery

Student partially discussed the implications of the article for social work practice specific to how the research evidence can improve the practice setting for state and local policy and service delivery

Student was proficient in discussing the implications of the article for social work practice specific to how the research evidence can improve the practice setting for state and local policy and service delivery

Student was exceptional in discussing the implications of the article for social work practice specific to how the research evidence can improve the practice setting for state and local policy and service delivery

Student discuss their critical assessment and opinion of article

(1 full page)

Student failed to discuss their critical assessment and opinion of article

(less than ½ page)

Student partially discussed their critical assessment and opinion of article (less than ¾ page)

Student was proficient in discussing their critical assessment and opinion of article ( ¾ page)

Student was exceptional in discussing their critical assessment and opinion of article (1 full page)

Student provide summary that discuss the research methods used (example: quantitative or qualitative, etc.) and the research findings of the author

Competency: 4: b

Student failed to provide a summary that discussed the research methods used (example: quantitative or qualitative, etc.) and the research findings of the author

Student partially provided a summary that discussed the research methods used (example: quantitative or qualitative, etc.) and the research findings of the author

Student was proficient in providing a summary that discussed the research methods used (example: quantitative or qualitative, etc.) and the research findings of the author

Student was exceptional in providing a summary that discussed the research methods used (example: quantitative or qualitative, etc.) and the research findings of the author

SUBTOTAL



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