ArticlePDF Available

Relations of Personality to Substance Use Problems and Mental Health Disorder Symptoms in Two Clinical Samples of Adolescents

Authors:

Abstract and Figures

There is a high overlap between substance misuse and mental health disorders in adolescents. Certain personality traits (i.e., sensation seeking, impulsivity, hopelessness, and anxiety sensitivity) may be related to increased risk for mental health symptoms and/or substance misuse. The current study examined the relationships between personality and both substance use problems and externalizing and internalizing mental health symptoms in two clinical samples of adolescents. One sample consisted of adolescents receiving treatment for a primary mental health disorder, while the other sample included adolescents receiving treatment for a primary substance use disorder. A total of 116 participants (58 for each sample) completed the Substance Use Risk Profile Scale (SURPS), to examine personality factors, the Brief Child and Family Phone Interview-Self-Report, to examine mental health disorder symptoms, and the Personal Experience Screening Questionnaire, to examine substance use problems. After controlling for age, gender, and sample, sensation seeking and impulsivity were positively related to substance use problems, impulsivity was posi-tively related to symptoms of externalizing disorders, and anxiety sensitivity and hopeless-ness were positively related to symptoms of internalizing disorders. These findings support the utility of the SURPS in predicting theoretically relevant symptoms in clinical samples of adolescents. Moreover, they extend previous research that has focused on using the SURPS as a predictor of substance misuse to its utility in also predicting mental health disorder symptoms. These findings have implications for improving mental health and addictions treatment services for adolescents.
Content may be subject to copyright.
Relations of Personality to Substance Use Problems
and Mental Health Disorder Symptoms in Two Clinical
Samples of Adolescents
Susan R. Battista & Alissa Pencer & Melissa McGonnell &
Heather Durdle & Sherry H. Stewart
Published online: 31 July 2012
#
Springer Science+Business Media, LLC 2012
Abstract There is a high overlap between substance misuse and mental health disorders in
adolescents. Certain personality traits (i.e., sensation seeking, impulsivity, hopelessness, and
anxiety sensitivity) may be related to increased risk for mental health symptoms and/or
substance misuse. The current study examined the relationships between personality and
both substance use problems and externalizing and internalizing mental health symptoms in
two clinical samples of adolescents. One sample consisted of adolescents receiving treatment
for a primary mental health disorder, while the other sample included adolescents receiving
treatment for a primary substance use disorder. A total of 116 participants (58 for each
sample) completed the Substance Use Risk Profile Scale (SURPS), to examine personality
factors, the Brief Child and Family Phone Interview- Self-Report, to examine mental health
disorder symptoms, and the Personal Experience Screening Questionn aire, to examine
substance use problems. After controlling for age, gender, and sample, sensation seeking
and impulsivity were positively related to substance use problems, impulsivity was posi-
tively related to symptoms of externalizing disorders, and anxiety sensitivity and hopeless-
ness were positively related to symptoms of internalizing disorders. These findings support
the utility of the SURPS in predicting theoretically relevant symptoms in clinical samples of
adolescents. Moreover, they extend previous research that has focused on using the SURPS
as a predictor of substance misuse to its utility in also predicting mental health disorder
symptoms. These findings have implications for improving mental health and addictions
treatment services for adolescents.
Keywords Substance use problems
.
Mental health
.
Adolescents
.
Personality
Int J Ment Health Addiction (2013) 11:112
DOI 10.1007/s11469-012-9395-0
S. R. Battista
:
A. Pencer
:
M. McGonnell
:
H. Durdle
:
S. H. Stewart (*)
Department of Psychology, Dalhousie University, Halifax, Nova Scotia, Canada B3H 4J1
e-mail: sstewart@dal.ca
A. Pencer
:
H. Durdle
IWK Health Centre, Halifax, Nova Scotia, Canada
A. Pencer
:
S. H. Stewart
Department of Psychiatry, Dalhousie University, Halifax, Nova Scotia, Canada B3H 4J1
The co-occurrence of mental health disorders and Substance Use Disorders (SUDs) is
common in treatment-seeking adolescents (e.g., Chan et al. 2008; Kramer et al. 2003 ). For
example, among adolescents younger than 15 years who were receiving treatment for an
SUD, 71.6 % had at least one co-occurring mental health disorder; the percentage was even
higher (82.3 %) among those aged 1517 years (Chan et al. 2008). Alternatively, among
adolescents p resenting for treatment of a mental health disorder, approximately 32 %
screened positive for an SUD (Kramer et al. 2003). In contrast, less than 3 % of adolescents
in the general community have an SUD (Roberts et al. 2009).
Moreover, adolescents with co morbid mental health and SUDs have overall greater
impairment than those with a mental health disorder alone (King et al. 2000). These greater
levels of impairment are not simply the result of having additional mental health diagnoses,
but rather, are specific to having a comorbid SUD. These findings suggest the need for
integrated treatments that address both mental health and SUDs in tandem (Canadian Centre
on Substance Abuse 2009). A first step in designing such interventions is determining
whether there are factors that place certain youth at risk for the development of co-morbid
mental health and SUDs, as such factors might be appropriate intervention targets.
Pihl and Peterson (1995) developed a model outlining four distinct personality factors
that could lead to substance abuse and certain comorbid mental health disorders. Their
model proposes that disturbances in specific brain motivation systems place certain individ-
uals at greater risk for seeking out and experiencing reinforcement from specific substances.
These four personality risk factors are: (a) Sensation Seeking (SS) (the desire for novel or
intense experiences; Zuckerman 1994); (b) Impulsivity (a tendency to act without careful
deliberation, reflection, or foresight; Dawe and Loxton 2004); (c) Anxiety Sensitivity (AS)
(the fear of anxiety-related sensations due to the belief that they could lead to harmful
consequences; Reiss et al. 1986) and (d) Hopelessness (the expectation that desirable events
will not occur or that aversive events will occur; Abramson et al. 1989).
Theoretically, those high in SS may be more likely to use drugs because of an increased
sensitivity to drug effects on the dopamine brain reward system. Individuals with a tendency
to be impulsive are thought to have deficits in the serotonin system, and consequent
difficulties with self regulation, which may lead to increased risk for stimulant misuse and
comorbid externalizing disorders. Those with high levels of AS may have deficits in their
Gamma-Aminobutyric acid (GABA) neurochemical pathways that result in dysfunction in
the fear motivation system, which makes them prone to abuse anxiolytic drugs and vulner-
able to comorbid anxiety disorders. Individuals high in hopelessness are said to be sensitive
to the threat of punishment as a result of deficits in the endogenous opiate system. They are
hypothesized to be at risk for using drugs that have analgesic effects (e.g., heroin and other
narcotics) and comorbid mood disorders.
Research with non-clinical adolescents indicates that those who score higher on SS tend
to use substances more often than those who score lower on such measures (e.g., Gerra et al.
2004). Similarly, SS has been shown to predict future alcohol, marijuana, tobacco, and
hallucinogen use in non-clinical adolescents (Krank et al. 2011). Some research indicates
that SS may also be positively associated with externalizing disorders such as attentional and
conduct problems (e.g., Ang and Woo 2003).
Similar to SS, impulsivity has been linked to a tendency to engage in risky behaviours,
including substance use, in non-clinical adolescents (e.g., Donohew et al. 2004). Moreover,
after accounting for the effects of SS and initial substance use, impulsivity has been shown
to predict future alcohol, tobacco, and hallucinogen use in non-clinical adolescents (Krank et
al. 2011). Impulsivity has also been linked to greater occurrences of externalizing problems
(e.g., Bogg and Finn 2010).
2 Int J Ment Health Addiction (2013) 11:112
The relationship between AS and substance use is less clear in adolescents. Krank et al.
(2011) found that although AS was associated with concurrent lower levels of substance use,
it did not predict substance use measured 1 year later. However, Woicik et al. (2009) found
AS was associated with greater alcohol problems. Additionally, AS has been found to be a
risk factor for the development of anxiety disorders in adolescents (McLaughlin et al. 2007).
Finally, higher levels of hopelessness were found to be concurrently associated with an
increased likelihood of using alcohol, marijuana, tobacco, hallucinogens, and stimulants
(Krank et al. 2011). Hopelessness was also found to independently predict the us e of
marijuana, tobacco, and hallucinogens measured 1 year later (Krank et al. 2011). Hopeless-
ness has also been linked to depression in a number of studies (e.g., Joiner 2000).
In order to more specifically investigate the Pihl and Peterson (1995), the Substance Use
Risk Profile Scale (SURPS; Woicik et al. 2009) was developed to measure the models four
dimensions of personality. This measure has been validated in a number of non-clinical
samples, including a large sample of adolescents where it was found that the dimensions
were associated with specific substance use motives and patterns of substance use (Woicik et
al. 2009). Specifically, SS , impulsivity, and hopelessness were all positively related to
quantity and frequency of drinking, frequency of binge drinking, and severity of alcohol
problems. AS was not related to frequency or quantity of drinking but was positively related
to severity of alcohol problems. Further, all personality factors with the exception of AS,
were positi vely related to other substance use, with SS demonstrating the strongest
relationships.
Although these general population findings provide initial support for the possibility that
all four personality characteristics may place certain adolescents at risk for SUDs, these
relationships have yet to be examined in clinical populations of adolescents. Moreover, no
published research to date has examined the relations of the SURPS personality factors with
mental health disorder symptoms although such associations are predicted in the Pihl and
Peterson (1995) model. Therefore, the current study examined two clinical samples of
adolescents to determine if findings from non-clinical samples of adolescents extended to
adolescents who are actively receiving treatment.
This research is important given that previous findings from the SURPS in non-clinical
samples (Woicik et al. 2009; Krank et al. 2011) may not necessarily generalize to clinical
samples where more extreme scores are likely to be found. It is important to know the utility
of this measure before it can be used for assessment and treatment planning in clinical
settings. It is possible that the SURPS may prove even more predictive in clinical samples
(e.g., certain thresholds may be necessary on the SURPS in order for scores to be predictive
of substance use problems/mental health symptoms, and such thresholds are more likely to
be surpassed in clinical samples than in the general population). Alternatively, it is possible
that the predictive utility of the SURPS will be diminished in clinical settings if there is
range restriction on the predictor (SURPS) and/or outcomes (mental health/substance use
problems) in clinical samples relative to the general population.
One goal of the current study was to examine the link between each of the four SURPS
personality characteristics and substance use problems. Based on theory and relevant
research, it was hypothesized that all four personality characteristics would be positively
related to substance use problems (e.g., Pihl and Peterson 1995; Woicik et al. 2009). A
second goal was to determine how each personality factor related to externalizing and
internalizing mental health disorder symptoms. It was hypothesized that SS and impulsivity
would be positively related to externalizing disorder symptoms (e.g., Bogg and Finn 2010),
while AS and hopelessness would be positively related to internalizing disorder symptoms
(e.g., Joiner 2000; McLaughlin et al. 2007).
Int J Ment Health Addiction (2013) 11:112 3
Method
Participants
One hundred and sixteen adolescents (51 males, 65 females) took part in the current study.
Participants ranged in age from 12 to 19 (M0 16.03, SD0 1.52) and most were White (72 %).
Participants were recruited from four outpatient community mental health centres. Three of
them treat adolescents whose primary presenting problems are mental health disorders. A
total of 58 adolescents (17 males, 41 females) were recruited from these three centres. These
participants ranged in age from 12 to 18 years (M0 15.90, SD0 1.54) and the majority (76 %)
were White. The fourth outpatient community mental health centre focuses primarily on the
treatment of adolescent SUDs. A total of 58 adolescents (34 males, 24 females) from this
service took part in the current study. These participants ranged in age from 13 to 19 years
(M0 16.17, SD0 1.49) and the majority (67 %) were White. A ll study measures were
completed during the course of participants treatment.
1
Measures
The Substance Use Risk Profile Scale (SURPS; Woicik et al. 2009) The SURPS is a 23-item
measure designed to assess personality risk factors for substance use problems. It contains
four subscales: Sensation Seeking (SS; 6 items), Impulsivity (5 items), Anxiety Sensitivity
(AS; 5 items), and Hopelessness (7 items). Each of the SURPS scales has shown good factor
structure and convergent validity in a large, non-clinical sample of adolescents (Woicik et al.
2009). The SURPS has also shown good predictive validity in explaining increases in
substance use/problems over a 1 year interval in a large non-clinical sample of adolescents
(Krank et al. 2011). Reliabilities for each subscale ranged from adequate to good (alpha 0
.67.85) in the current study.
The Personal Experience Screening Questionnaire- Problems Subscale (PESQ; Winters
1992) This self-report measure was specifically designed for assessing substance use in
adolescents. For the current study, only the subscale designed to measure substance use
problems was examined. This subscale includes 21 items which measure the frequency of
problems related to substance use (e.g., made excuses to teachers about your alcohol or drug
use) on a 4-point scale ranging from 1 (never)to4(often). This measure has demonstrated
good internal consistency and discriminant validity across a number of samples (Winters
1992). In the current study, the substance use problems scale demonstrated excellent
reliability (alpha 0 .96).
The Brief Child and Family Phone Interview (BCFPI-3; Paper-and-Pencil Adolescent Self-
Report Version; Cunningham et al. 2009) This questionnaire consists of 36 items designed
to screen for the presence and severity of a number of mental health disorder symptoms. In
the present study, T-scores were calculated for two 18 item scales: overall Internalizing
symptoms (which includes Separation Anxiety, Anxiety, and Mood Disorder items) and
overall Externalizing symptoms (which includes Attention, Conduct, and Cooperativeness
problems items). This measure has been widely used in Canadian health care settings for
screening, triaging, service planning, and outcome evaluation of adolescent mental health
disorders (e.g., Cunningham e t al. 2007). The telephone version of this measure has
1
Information on socio-economic status, clinical diagnoses, and stage of treatment was not collected.
4 Int J Ment Health Addiction (2013) 11:112
demonstrated strong internal consistency for the Externalizing and Internalizing subscales
(alpha 0 .85 and .87, respectively; Cunningham et al. 2009) and adequate test-retest
reliability (subscale rs of .50 for both the Externalizing and Internalizing subscales with
an interval of approximately 48 days; Boyle et al. 2009). In the current study, the overall
Externalizing and Internalizing scales had good to excellent reliability (alpha 0 .84 and .91,
respectively).
Procedure
Clients were informed of the study during their regular appointments by their therapists or by
viewing posters displayed around the clinics. If interested, clients completed a form,
providing their name and telephone number to the researchers. The researchers then con-
tacted clients and arranged times for them to complete the questionnaires. Alternatively,
some participants were recruited during group programs where the researchers told clients
about the study and then those who were interested stayed after the group to complete the
questionnaires. Finally, some participants completed the questionnaires while they were
waiting for their scheduled appointments. After obtaining written informed consent, all
questionnaires were presented in counter-balanced order and completed by participants in
a single sitting. Participants received a $10 movie pass as compensation.
Results
A Comparison of Study Measures Across Samples
As shown in Table 1, participants recruited from community mental health clinics (mental
health sample) were more likely to be female than participants recruited from the adolescent
substance misuse centre (substance misuse sample), χ
2
(116) 0 10.11, p0 .001, and had
lower self-reported levels of Externalizing symptoms, t (114) 0 3.26, p0 .001. The mental
health sample reported fewer substance use problems, t (114) 0 9.90, p <.001, and
significa ntly lower levels of SS, t (114) 0 3.48, p0 .001, and Impulsivity, t (114) 0
4.42, p<.001, but higher levels of AS, t (114) 0 2.00, p<.05, than the substance misuse
sample. Given these differences, all regression analyses controlled for sample.
Bivariate Correlations
Bivariate correlations were computed between all study measures (see Table 2). Age was
positively correlated with substance use problems. Girls scored higher than boys on both
BCFPI scales and on Hopelessness and AS whereas boys scored higher than girls on SS.
Sample was correlated with a number of study measures as described in the previous section.
Additionally, SS was correlated with substance use problems while Impulsivity was corre-
lated with substance use problems and Externalizing symptoms. Hopelessness was correlated
with both BCFPI scales while AS was associated with Internalizing symptoms.
Hypothesis Testing
Hierarchical regressions were conducted to examine whether personality scores pre-
dicted substance use problems and/or mental health symptoms above and beyond
other relevant variables. In a ll analyses, demographic variables (age and gender where
Int J Ment Health Addiction (2013) 11:112 5
1 0 male and 2 0 female
)2
were entered as a block into Step 1. Given differences found between
the substance misuse sample and the mental health sample (see Table 1), sample (where 1 0
mental health sample and 2 0 substance misuse sample) was entered at Step 2. Finally, all four
SURPS personality scores (SS, Impulsivity, AS, and Hopelessness) were entered as a block into
Step 3. Please see Table 3 where the final step of each regression is summarized.
Predicting Substance Use Problems
Step 1 of the regression was significant, F (2, 113) 0 5.12, p<.01, with demographic
variables accounting for 6.7 % of the variance in substance use problems. Older age was the
only significant predictor at this step. Step 2 was also significant, Δ F (1, 112) 0 93.86, p<.001,
with sample accounting for an additional 41.8 % of the variance above and beyond demo-
graphic variables. At this step, older age and being a member of the substance misuse sample
proved significant independent predictors of greater substance use problems. Finally, Step 3
was also significant, Δ F (4, 108) 0 3.80, p<.01, with the block of SURPS personality variables
accounting an additional 6.2 % of the variance above and beyond demographics and sample.
The final model was significant (F (7, 108) 0 19.86, p<.001), with age, sample and as
2
Ethnicity was not found to correlate with any study variable and therefore was not included as a demo-
graphic control variable in the regression analyses.
Table 1 Comparison of demographics and study measures across samples
Mental health sample Substance misuse sample
MSDRange % in clinical
range
MSDRange % in clinical
range
Demographics:
Age (in years) 15.90 1.54 1218 16.17 1.49 1319
Gender 71 % female** 41 % female**
BCFPI subscales:
Externalizing
symptoms
62.38** 10.99 3788 17.20 69.52** 12.57 45110 48.30
Internalizing symptoms 62.76 12.27 3586 31.00 59.53 12.51 3582 22.40
PESQ:
Substance use
problems
30.47** 14.65 1872 31.00 52.78** 8.93 3572 100.00
SURPS subscales:
Sensation seeking 15.28** 3.94 723 17.61** 3.26 1124
Impulsivity 11.74** 3.01 518 13.88** 2.14 919
Anxiety sensitivity 12.48* 3.26 520 11.28* 3.23 519
Hopelessness 15.64 4.85 728 16.28 3.71 725
BCFPI Brief Child and Family Phone Inventory (Cunningham et al. 2009) where >70 is in the clinical range;
PESQ Personal Experiences Questionnaire (Winters 1992) where clinical norms are as follows: Males 1215
>30, Males 1618>35, Females 1215>30, Females 1618>34; SURPS Substance Use Risk Profile Scale
(Woicik et al. 2009, clinical norms not available)
Between-sample differences indicated via asterisks: * p<.05. ** p<.01
6 Int J Ment Health Addiction (2013) 11:112
hypothesized, SS and Impulsivity proving significant independent predictors of substance use
problems. However, contrary to hypotheses, AS and Hopelessness were not related to substance
use problems when considering other relevant variables.
Table 3 Summary of final hierarchical regression models
Outcome variable Predictor variables BSEBβ tp-value
Substance use problems Age 2.28 .72 .21 3.18 .002**
Sex 2.32 2.42 .07 .96 .340
Sample 18.11 2.47 .55 7.34 .000***
SURPS Hopelessness .01 .26 .00 .04 .970
SURPS Sensation Seeking .66 .31 .15 2.16 .033*
SURPS Impulsivity 1.12 .44 .19 2.59 .011**
SURPS Anxiety Sensitivity .25 .35 .05 .70 .483
Externalizing symptoms Age .28 .61 .03 .45 .652
Sex 7.94 2.07 .32 3.84 .000***
Sample 4.23 2.10 .17 2.01 .047*
SURPS Hopelessness .25 .22 .09 1.13 .263
SURPS Sensation Seeking .27 .26 .08 1.02 .307
SURPS Impulsivity 1.96 .37 .45 5.28 .000***
SURPS Anxiety Sensitivity .14 .30 .04 .46 .644
Internalizing symptoms Age .47 .57 .06 .83 .409
Sex 2.85 1.92 .11 1.48 .141
Sample 2.51 1.96 .10 1.28 .204
SURPS Hopelessness 1.39 .20 .48 6.82 .000***
SURPS Sensation Seeking .34 .25 .10 1.38 .170
SURPS Impulsivity .11 .35 .02 .31 .756
SURPS Anxiety Sensitivity 1.60 .28 .42 5.79 .000***
SURPS Substance Use Risk Profile Scale (Woicik et al. 2009); * p .05, ** p .01, ***p .001
Table 2 Bivariate correlations between study measures
12345678910
1. Age .07 .09 .25** .02 .14 .06 .03 .06 .16
2. Gender .30** .16 .27** .33** .29** .04 .21* .29**
3. Sample .68** .29** .13 .31** .38** .08 .19*
4. Substance use problems .37** .05 .38** .44** .11 .11
5. Externalizing .28** .17 .57** .27** .06
6. Internalizing .02 .17 .52** .48**
7. Sensation-seeking .27** .00 .17
8. Impulsivity .23* .08
9. Hopelessness .03
10. Anxiety sensitivity ––
Gender coded as 1 0 male, 2 0 female; Sample coded as 1 0 mental health, 2 0 substance misuse; * p<.05. **
p<.01
Int J Ment Health Addiction (2013) 11:112 7
Predicting Externalizing Mental Health Symptoms
Step 1 of the regression was significant, F (2, 113) 0 4.54, p0 .01, with demographic
variables accounting for 5.8 % of the variance. Female gender was the only significant
predictor of Externalizing symptoms at this step. Step 2 was also significant, Δ F (1, 112) 0
21.63, p<.001, with sample accounting for an additional 15.0 % of the variance above and
beyond demograph ic variables. At this step, being female and being a member of the
substance misuse sample proved significant independent predictors of greater Externalizing
problems. Finally, Step 3 was also significant, Δ F (4, 108) 0 9.62, p<.001, with the block
of SURPS personality variables accounting an additional 20.4 % of the above and beyond
demographics and sample. The final model was significant (F (7, 108) 0 11.55, p<.001),
with female gender, sample and as hypothesized, Impulsivity proving significant indepen-
dent predictors of Externalizing symptoms. However, contrary to hypotheses, SS was not
related to Externalizing symptoms when considering other relevant variables.
Predicting Internalizing Mental Health Symptoms
Step 1 of the regression was significant, F (2, 113) 0 9.04, p<.001, with demographic
variables accounting for 12.3 % of the variance. Being female was the only significant
predictor of Internalizing symptoms at this step. Step 2 was not significant, indicating that
sample did not predict Internalizing symptoms above and beyond demographic variables.
Finally, Step 3 was significant, Δ F (4, 108) 0 20.98, p<.001, with the block of SURPS
personality variables accounting an additional 37.6 % of the variance above and beyond
demographics and sample. The final model was significant (F (7, 108) 0 16.45, p<.001). As
hypothesized, Hopelessness and AS proved significant independent predictors of Internal-
izing symptoms.
Discussion
The current study examined the relationships between personality variables in the Pihl and
Peterson (1995) model and substance use problems as well as mental health symptoms in
adolescents receiving treatment. As hypothesized, SS and impulsivity independently predicted
substance use problems. Previous research has supported a relationship between both SS and
impulsivity and frequency of substance use (Krank et al. 201 1) and severity of drinking problems
(Woicik et al. 2009). The current findings extend these findings to substance use problems in
adolescents actively receiving treatment for either a substance use or mental health problem.
Another finding that emerged was the lack of an association between hopelessness and
substance use problems. Previous studies have found hopelessness to be positively associ-
ated with frequency of substance use (e.g., Krank et al. 2011) and with problematic drinking
(Woicik et al. 2009) in non-clinical samples of adolescents. One potential explanation for
these discrepant findings may be that hopelessness plays a greater role in the initiation of
problematic substance use (e.g., in non-clinical samples), rather than the maintenance of
problematic use (e.g., in clinical samples). It could also be that the relations of impulsivity
and SS with problematic substance use are stronger than between hopelessness and prob-
lematic substance use and thus larger sample sizes may be required to provide adequate
power to detect relations of hopelessness with problematic substance use. Finally, it could be
that, consistent with Pihl and Petersons(1995) model, hopelessness is more specifically
related to problems with analgesic substance use (e.g., prescription opioids, heroin).
8 Int J Ment Health Addiction (2013) 11:112
Further, no significant connections were found between AS and substance use problems.
This is inconsistent with past findings, which have pointed towards AS as a risk factor for
substance problems (e.g., Woicik et al. 2009). However, previous studies examined non-
clinical samples of adolescents and thus, more research is needed to examine the role of AS
in substance use in clinical adolescents. Future research should examine relations of AS with
substance use motives and with particular types of substance problems that theoretically may
be more likely to be associated with AS than others (e.g., experience of substance with-
drawal vs. getting in fights). Another possibility is that, consistent with Pihl and Petersons
(1995) theory, AS may be specifically linked with problems with anxiolytic substances (e.g.,
benzodiazepines, alcohol).
In regards to mental health symptoms, impulsivity was found to be an independent
predictor of externalizing symptoms while hopelessness and AS were found to be indepen-
dently related to internalizing symptoms. Unexpectedly, SS was not found to be related to
externalizing symptoms. Although previous research has found SS to be associated with
externalizing symptoms (e.g., Ang and Woo 2003), a recent study by Castellanos-Ryan and
Conrod (2011) found that SS was not related to overall externalizing behaviors but rather
was specifically related to substance use in a non-clinical sample. The current findings
extend this result to a clinical sample of adolescents.
Inconsistencies in the literature regarding the relation of SS to externalizing disorder
symptoms may be related to how SS is measured. Some theories and instruments assess a
composite construct known as impulsive sensation seeking (Zuckerman and Kuhlman
2000). Our findings suggest that separate assessment of SS and impulsivity is useful since
only impulsivity was related to both externalizing symptoms and substance use problems,
while SS was more specifically linked to substance use problems (see also Castellanos-Ryan
and Conrod 2011).
AS and hopelessness were both independently related to overall internalizing symptoms
as would be expected based on past findings (e.g., Joiner 2000; McLaughlin et al. 2007 ). It
would be important in future studies to look more specifically at the relations between AS
and anxiety d isorder symptoms versus hopelessness and mood disorders symptoms to
determine if these personality scales are related to specific mental health symptoms as is
predicted by theory.
Although the two samples were comparable on some variables, there were some signif-
icant differences between them. However, sample was controlled for in order to account for
these differences and the SURPS was still found to be useful in predicting substance use
problems and mental health symptoms. This further supports the utility of the SURPS in
adolescents who present to either type of treatment setting. It was also found that females
had higher levels of internalizing and externalizing sympto ms than males. Regarding
internalizing concerns, this is consistent with past findings using the BCFPI (e.g., Cunning-
ham et al. 2009). However, the finding that females also scored higher on the externalizing
scale is unexpected and contrary to previous findings that have typically found the opposite
(e.g., Cunningham et al. 2009). The reason for this discrepancy is unclear and may have
been due to a response bias where females may have felt more comfortable than males in
reporting their symptoms in the presence of a female research assistant. Regardless, the
SURPS was still predictive of mental health symptoms and substance use problems after
controlling for gender differences.
There are some limitations in the current study that should be noted. First, the study used
a cross-sectional design, which limits the ability to determine if any of the aforementioned
relations are causal. While Phil and Petersons(1995) theory argues that personality causes
increased risk for substance use/mental health symptoms, the opposite is also possible. For
Int J Ment Health Addiction (2013) 11:112 9
example, chronic substance misuse could increase impulsivity (e.g., Gruber et al. 2011).
Alternatively, there may be reciprocal relations between personality and substance use/
mental health (see Marshall et al. 2010). A longitudinal design would be necessary to help
determine if personality prospectively predicts substance use problems/mental health symp-
toms in a clinical sample of adolescents. Further, it is unknown at which stage of treatment
participants completed the study measures. Both the PESQ and BCFPI do not specify a time
frame so it is certainly possible that relevant substance use problems and/or mental health
symptoms may have decreased due to treatment in some participants. Future research should
aim to investigate adolescents at a similar stage of treatment (e.g., at intake) or control for
stage of treatment in the analyses. Finally, the current study focused on substance use
problems rather than substance use frequency and therefore, it is unknown how personality
factors relate to different frequencies or intensities (i.e., doses) of substance use. Future
research would benefit by more specifically measuring levels (i.e., frequency, dose) and
types (e.g., stimulants vs. anxiolytics vs. analgesics) of substance use, rather than looking at
substance use generically (i.e., problems collapsed across substance type).
In sum, the current study suggests that certain personality factors may be associated with
substance problems and/or mental health disorder symptoms in clinical adolescents. Given
numerous findings indicating that SUDs and mental health disorder symptoms co-occur
(e.g., Chan et al. 2008), and the current study findings that demonstrate high levels of mental
health symptoms in adolescents receiving treatment for substance misuse and high levels of
substance use problems in adolescents receiving treatment for mental health symptoms, it is
important to consider how treatment programs can be developed to meet the needs of
individuals experiencing symptoms in both of these areas. The current findings suggest that
there are some common personality factors that may be useful in co nceptualizing and
designing treatment programs for co-occurring substance use and mental health symptoms.
Specifically, this study suggests that impulsivity may be associated with both substance use
problems and externalizing symptoms, while SS may be a risk factor specifically for
substance use problems. Hopelessness and AS may be risk factors for internalizing symp-
toms rather than general substance problems. As such, a treatment targeting impulsivity may
be most appropriate for clinical adolescents with co-occurring substance use and external-
izing symptoms (e.g., focusing on techniques to help them manage impulsivity to decrease
involvement in risky behaviours). On the other hand, targeting hopelessness and AS would
be useful in adolescents with internalizing disorder symptoms (e.g., focusing on cognitive
restructuring and behavioral activation). Moreover, a treatment targeting SS may be partic-
ularly useful in adolescents with substance use problems alone. Such brief treatments have
been found to be effective in reducing substance use/misuse (Conrod et al. 2006 , 2011) and
mental health disorder symptoms (e.g., Castellanos and Conrod 2006)innon-clinical
samples. However, more research is needed to establish whether these brief targeted treat-
ments lead to improvements in mental health and/or substance use/misuse in clinical
samples. Moreover, it would be important to determine if these brief treatments are sufficient
or if they need to be extended given the sever ity of problems experienced in clinical
adolescents, and if such treatments should be used as stand-alone treatments or as adjuncts
to existing treatments.
Acknowledgments Funding for this project was provided by an IWK Category A Grant and a Dalhousie
Psychiatry Research Fund Grant. The first author is currently supported by a Nova Scotia Health Research
Foundation Student Research Award. Both the first and third author were supported by Social Sciences and
Humanities Research Council Doctoral Scholarships, while the final author was supported by a Killam
Research Professorship from the Dalhousie University Faculty of Science, at the time this research was
10 Int J Ment Health Addiction (2013) 11:112
conducted. The authors gratefully acknowledge Javad Alaghband-rad, Shannon Barnsley, Anne Brochu,
Fiona Davidson, Sarah Doucette, Ann Marie Joyce, Christa Peters, and Lee Simpson for their help with this
project.
References
Abramson, L. Y., Metalsky, G. I., & Alloy, L. B. (1989). Hopelessness depression: A theory-based subtype of
depression. Psychological Review, 96(2), 358372. doi:10.1037/0033-295X.96.2.358.
Ang, R. P., & Woo, A. (2003). Influence of sensation seeking on boys psychosocial adjustment. North
American Journal of Psychology, 5(1), 121136. Retrieved from EBSCOhost.
Bogg, T., & Finn, P. R. (2010). A self-regulatory model of behavioral disinhibition in late adolescence:
Integrating personality traits, externalizing psychopathology, and cognitive capacity. Journal of Person-
ality, 78(2), 441470. doi:10.1111/j.1467-6494.2010.00622.x.
Boyle, M. H., Cunningham, C. E., Georgiades, K., Cullen, J., Racine, Y., & Pettingill, P. (2009). The Brief Child
and Family Phone Interview (BCFPI): II. Usefulness in screening for child and adolescent psychopathology.
Journal of Child Psychology and Psychiatry, 50(4), 424431. doi:10.1111/j.1469-7610.2008.01971.x.
Canadian Centre on Substance Abuse. (2009). Substance abuse in Canada: Concurrent disorders. Ottawa,
ON: Canadian Centre on Substance Abuse.
Castellanos, N., & Conrod, P. (2006). Brief interventions targeting personality risk factors for adolescent
substance misuse reduce depression, panic and risk-taking behaviours. Journal of Mental Health, 15(6),
645658. doi:10.1080/09638230600998912.
Castellanos-Ryan, N., & Conrod, P. J. (2011). Personality correlates of the common and unique variance
across conduct disorder and substance misuse symptoms in adolescence. Journal of Abnormal Psychol-
ogy, 39(4), 563576. doi:10.1007/s10802-010-9481-3.
Chan, Y., Dennis, M. L., & Funk, R. R. (2008). Prevalence and comorbidity of major internalizing and
externalizing problems among adolescents and adults presenting to substance abuse treatment. Journal of
Substance Abuse Treatment, 34(1), 1424. doi:10.1016/j.jsat.2006.12.031.
Conrod, P. J., Castellanos-Ryan, N., & Mackie, C. (2011). Long-term effects of a personality-targeted
intervention to reduce alcohol use in adolescents. Journal of Consultin g and Clinical Psychology.
doi:10.1037/a0022997.
Conrod, P. J., Stewart, S. H., Comeau, N., & Maclean, A. (2006). Efficacy of cognitive-behavioral inter-
ventions targeting personality risk factors for youth alcohol misuse. Journal of Clinical Child and
Adolescent Psychology, 35(4), 550563. doi:10.1207/s15374424jccp3504_6.
Cunningham, C. E., Boyle, M. H., Hong, S., Pettingill, P., & Bohaychuk, D. (2009). The Brief Child and
Family Phone Interview (BCFPI): I. Rationale, development, and description of a computerized child-
rens mental health intake and outcome assessment tool. Journal of Child Psychology and Psychiatry, 50
(4), 416423. doi:10.1111/j.1469-7610.2008.01970.x.
Cunningham, C. E., Harrison, R., Knight, R., McHolm, A., Pollard, L., Ricketts, P. (2007). The Brief Child
and Family Phone Interview (BCFPI) in Hamilton: Intake Screening, triaging, outcome measurement, and
program management. Psychology Ontario,810. http://tinyurl.com/d4dzur
.
Dawe, S., & Loxton, N. J. (2004). The role of impulsivity in the development of substance use and eating
disorders. Neuroscience and Biobehavioral Reviews, 28(3), 343351. doi:10.1016/j.neubiorev.2004.03.007.
Donohew, L. L., Bardo, M. T., & Zimmerman, R. S. (2004). Personality and risky behavior: Communication
and prevention. In R. M. Stelmack (Ed.), On the psychobiology of personality: Essays in honor of Marvin
Zuckerman (pp. 223245). New York, NY: Elsevier Science. doi:10.1016/B978-008044209-9/50014-2.
Gerra, G. G., Angioni, L. L., Zaimovic, A. A., Moi, G. G., Bussandri, M. M., Bertacca, S. S., &
Nicoli, M. A. (2004). Substance use among high-school students: Relationships with temperament,
personality traits, and parental care perception. Substance Use and Misuse, 39(2), 345367.
doi:10.1081/JA-120028493.
Gruber, S. A., Silveri, M. M., Dahlgren, M., & Yurgelun-Todd, D. (2011). Why so impulsive? white matter
alterations are associated with impulsivity in chronic marijuana smokers. Experimental and Clinical
Psychopharmacology, 19(3), 231242. doi:10.1037/a0023034.
Joiner, T. R. (2000). A test of the hopelessness theory of depression in youth psychiatric inpatients. Journal of
Clinical Child Psychology, 29(2), 167176. doi:10.1207/S15374424jccp2902_3.
King, R. D., Gaines, L. S., Lambert, E., Summerfelt, W., & Bickman, L. (2000). The co-occurence of
psychiatric substance use diagnoses in adolescents in different service systems: Frequency, recognition,
cost, and outcomes. Journal of Behavioral Health Services and Research, 27(4), 417430. doi:10.1007/
BF02287823.
Int J Ment Health Addiction (2013) 11:112 11
Kramer, T. L., Robbins, J. M., Phillips, S. D., Miller, T. L., & Burns, B. J. (2003). Detection and outcomes of
SUDs in adolescents seeking mental health treatment. Journal of the American Academy of Child and
Adolescent Psychiatry, 42(11), 13181326. doi:10.1097/01.chi.0000084833.67701.44.
Krank, M., Stewart, S. H., O'Connor, R., Woicik, P. B., Wall, A., & Conrod, P. J. (2011). Struct ural,
concurrent, and predictive validity of the Substance Use Risk Profile Scale in early adolescence. Addictive
Behaviors, 36(12), 3746. doi:10.1016/j.addbeh.2010.08.010.
Marshall, G. N., Miles, J. V., & Stewart, S. H. (2010). Anxiety sensitivity and PTSD symptom severity are
reciprocally related: Evidence from a longitudinal study of physical trauma survivors. Journal of
Abnormal Psychology, 119(1), 143150. doi:10.1037/a0018009.
McLaughlin, E. N., Stewart, S. H., & Taylor, S. (2007). Childhood Anxiety Sensitivity Index factors predict
unique variance in DSM-IV anxiety disorder symptoms. Cognitive Behaviour Therapy, 36(4), 210219.
doi:10.1080/16506070701499988.
Pihl, R. O., & Peterson, J. B. (1995). Alcoholism: The role of different motivational systems. Journal of
Psychiatry and Neuroscience, 20(5), 372396. Retrieved from EBSCOhost.
Reiss, S., Peterson, R. A., Gursky, D. M., & McNally, R. J. (1986). AS, anxiety frequency, and the prediction
of fearfulness. Behaviour Research and Therapy, 24(1), 18. doi:10.1016/0005-7967(86)90143-9.
Roberts, R. E., Roberts, C. R., & Chan, W. (2009). One-year incidence of psychiatric disorders and associated
risk factors among adolescents in the community. Journal of Child Psychology and Psychiatry, 50(4),
405415. doi:10.1111/j.1469-7610.2008.01969.x.
Winters, K. C. (1992). Development of an adolescent alcohol and other drug abuse screening scale: Personal
Experience Screening Questionnaire. Addictive Behaviors, 17(5), 479490. doi:10.1016/0306-4603
(92)90008-J.
Woicik, P. A., Stewart, S. H., Pihl, R. O., & Conrod, P. J. (2009). The substance use risk profile scale: A scale
measuring traits linked to reinforcement-specific substance use profiles. Addictive Behaviors, 34(12),
10421055. doi:10.1016/j.addbeh.2009.07.001.
Zuckerman, M. (1994). Behavioral expressions and bio social bases of SS. New York, NY: Cambridge
University Press. Retrieved from EBSCOhost.
Zuckerman, M., & Kuhlman, D. (2000). Personality and risk-taking: Common biosocial factors. Journal of
Personality, 68(6), 9991029. doi:10.1111/1467-6494.00124.
12 Int J Ment Health Addiction (2013) 11:112
... The findings of the aforementioned study were also limited by a small sample size (N = 123), and thus specific predictors of group membership could not be examined. Research also suggests that personality factors are well-established predictors of alcohol misuse (Woicik et al. 2009) and depression (Battista et al. 2013;Joiner 2000;Taylor et al. 1996). Impulsivity, sensation seeking, hopelessness, and anxiety sensitivity have all been associated with unique patterns of alcohol misuse risk among emerging adults (Conrod and Nikolaou 2016). ...
Article
Full-text available
Alcohol misuse and depression are highly comorbid. Self-medication theory posits that depressed individuals use alcohol to reduce negative emotions. Research suggests that the co-pattern of depression and alcohol misuse is not uniform, and that emerging adults transitioning out of university can be differentiated into subgroups based on their co-patterns. We aimed to replicate and extend this study with emerging adults during university by examining whether baseline individual differences predicted subgroup membership. Undergraduates (N = 300) completed four waves of self-reports at 6-month intervals over 18-months. Parallel process latent class growth modeling supported three classes: Class 1, the 'high-risk comorbid' group, had high stable depression and high stable alcohol misuse (n = 28). Class 2, the 'moderate-risk depression-only group' had high stable depression but low decreasing alcohol misuse (n = 87). Class 3, the 'low-risk normative' group, had low stable depression and low decreasing alcohol misuse (n = 185). Multinomial regressions showed that male sex, higher hopelessness, impulsivity, and anxiety sensitivity, and higher coping-with-depression and enhancement drinking motives, differentiated Class 1 from Class 3. Higher impulsivity and lower hopelessness, and higher enhancement motives, differentiated Class 1 from Class 2. Higher hopelessness, and higher coping-with-depression and conformity motives, differentiated Class 2 from Class 3. We utilized a subclinical sample and a short follow-up period. Emerging adults display differing co-patterns of depression and alcohol misuse over time during university, including both high-, moderate-, and low-risk subgroups. Our results provide novel evidence subgroups that can be distinguished based on sex, drinking motives, and personality.
... The findings of the aforementioned study were also limited by a small sample size (N = 123), and thus specific predictors of group membership could not be examined. Research also suggests that personality factors are well-established predictors of alcohol misuse (Woicik et al. 2009) and depression (Battista et al. 2013;Joiner 2000;Taylor et al. 1996). Impulsivity, sensation seeking, hopelessness, and anxiety sensitivity have all been associated with unique patterns of alcohol misuse risk among emerging adults (Conrod and Nikolaou 2016). ...
Article
Full-text available
Alcohol misuse and depression are highly comorbid. Self-medication theory posits that depressed individuals use alcohol to reduce negative emotions. Research suggests that the co-pattern of depression and alcohol misuse is not uniform, and that emerging adults transitioning out of university can be differentiated into subgroups based on their co-patterns. We aimed to replicate and extend this study with emerging adults during university by examining whether baseline individual differences predicted subgroup membership. Undergraduates (N = 300) completed four waves of self-reports at 6-month intervals over 18-months. Parallel process latent class growth modeling supported three classes: Class 1, the “high-risk comorbid” group, had high stable depression and high stable alcohol misuse (n = 28). Class 2, the “moderate-risk depression-only group” had high stable depression but low decreasing alcohol misuse (n = 87). Class 3, the “low-risk normative” group, had low stable depression and low decreasing alcohol misuse (n = 185). Multinomial regressions showed that male sex, higher hopelessness, impulsivity, and anxiety sensitivity, and higher coping-with-depression and enhancement drinking motives, differentiated Class 1 from Class 3. Higher impulsivity and lower hopelessness, and higher enhancement motives, differentiated Class 1 from Class 2. Higher hopelessness, and higher coping-with-depression and conformity motives, differentiated Class 2 from Class 3. We utilized a subclinical sample and a short follow-up period. Emerging adults display differing co-patterns of depression and alcohol misuse over time during university, including both high-, moderate-, and low-risk subgroups. Our results provide novel evidence subgroups that can be distinguished based on sex, drinking motives, and personality.
... Much work has examined correlations between SURPS subscales and substance use outcomes, such as alcohol, tobacco, and cannabis use, as well as related problems, among adolescents (Battista, Pencer, McGonnell, Durdle, & Stewart, 2013;Lammers, Kuntsche, Engels, Wiers, & Kleinjan, 2013;Malmberg et al., 2012;Malmberg et al., 2015;Moser, Pearson, Hustad, & Borsari, 2014) and college students ( Barnes et al., 2014;Hustad, Pearson, Neighbors, & Borsari, 2014;Mackinnon, Kehayes, Clark, Sherry, & Stewart, 2014). For example, SS was found to be positively associated with peak blood alcohol content, and H with alcohol problems among college students (Moser et al., 2014). ...
Article
Full-text available
The Substance Use Risk Profile Scale (SURPS), a widely used self-report questionnaire, assesses four personality traits which predict risk for substance use (i.e., anxiety sensitivity, hopelessness, impulsivity, and sensation seeking). Given its use in research and clinical settings, as well as potential utility, this study aimed to provide a comprehensive psychometric evaluation of the SURPS. Undergraduate participants (N = 718; 69% White; 26% Hispanic, aged 18-25 years, M = 19.00, SD = 1.33) completed a battery of measures, including the SURPS. Tests of measurement invariance, convergent and criterion validity, and internal consistency were conducted, as well as item response theory analyses and a treatment assignment simulation. Several items were removed before partial measurement invariance across gender was established with little information lost. Despite removing several SURPS items, the proposed factor structure was not empirically supported. More work is necessary to determine the predictive utility of assessing these personality traits to predict substance-related outcomes.
... Means and standard deviations are presented in Table 1. Baseline means in Table 1 were compared to a sample seeking treatment for substance use disorder (Battista, Pencer, McGonnell, Durdle, & Stewart, 2013), a sample of adults seeking treatment for an alcohol use disorder (Mezquita et al., 2011) and an at-risk sample of college students seeking treatment for high-risk drinking behaviors (Schaus, Sole, McCoy, Mullett, & O'Brien, 2009). These clinical samples tended to have higher means on hopelessness (d ϭ 0.73), impulsivity (d ϭ 1.01), coping-depression motives (d ϭ 1.19), coping-anxiety motives (d ϭ 0.86), conformity motives (d ϭ 0.35), and RAPI totals (d ϭ 0.32), with ps Ͻ .05 ...
Article
Full-text available
The 4-factor model of personality vulnerability identifies 4 personality risk factors for alcohol misuse: hopelessness, anxiety sensitivity, impulsivity, and sensation seeking. These personality traits are associated with distinct mechanisms and motivations for alcohol misuse. Individuals high in hopelessness drink to regulate dysphoric affect, while those high in anxiety sensitivity drink to reduce anxiety and to conform to peer expectations. Individuals high in sensation seeking are highly sensitive to the rewarding properties of alcohol, and misuse alcohol to maximize enjoyment. Impulsivity is a broad risk factor contributing to all drinking motives. We hypothesized that personality vulnerabilities would indirectly predict alcohol quantity and problems through specific drinking motives theorized by the 4-factor model. The present study tested hypotheses using a 3-wave, 1-year longitudinal study of undergraduate drinkers (N 302). Data were analyzed using multilevel path analysis. Hopelessness and impulsivity were positively related to drinking motives in the expected fashion. Anxiety sensitivity was related to coping-anxiety and conformity motives only in the between-subjects model (partially supporting hypotheses), while sensation seeking was generally unrelated to all drinking motives and alcohol outcomes (failing to support hypotheses). Enhancement motives predicted alcohol quantity and problems at both levels, coping-depression motives predicted alcohol problems at the between-subjects level only, and coping-anxiety, conformity, and social motives failed to predict alcohol outcomes beyond other motives. Overall, this study partially supports the 4-factor model, with the strongest support emerging for impulsivity and hopelessness. This study suggests that personality traits such as impulsivity and hopelessness may be important targets in prevention and treatment with undergraduate drinkers.
... We measured both hazardous alcohol use and drinking harms (as opposed to just alcohol problems). Finally, most of the existing literature has looked at adolescents (Battista et al., 2013) or adults (Crutzen, Kuntsche, & Schelleman-Offermans, 2013). A renewed focus on undergraduates (who are approaching or have reached legal drinking age, who have moved away from home, and who have lost important social networks) is therefore warranted -given their elevated risk for problematic drinking (ACHA, 2016). ...
Article
Full-text available
Background: Rates of alcohol abuse are high on Canadian postsecondary campuses. Individual trait differences have been linked to indices of alcohol use/misuse, including neurotic traits like anxiety sensitivity (AS) and hopelessness (HOP). We know little, though, about how these traits confer vulnerability. AS and HOP are related to anxiety and depression, respectively, and to drinking to cope with symptoms of those disorders. Neurotic personality may therefore increase risk of alcohol use/abuse via (1) emotional disorder symptoms and/or (2) coping drinking motives. Objectives: Allan and colleagues (2014) found chained mediation through AS-generalized anxiety-coping motives-alcohol problems and AS-depression-coping motives-alcohol problems. We sought to expand their research by investigating how emotional disorder symptoms (anxiety, depression) and specific coping motives (drinking to cope with anxiety, depression) may sequentially mediate the AS/HOP-to-hazardous alcohol use/drinking harms relationships among university students. Methods: This study used cross-sectional data collected in Fall 2014 as part of the Movember-funded Caring Campus Project (N = 1,883). The survey included the SURPS, adapted DMQ-R SF, and AUDIT-3. Results: AS and HOP were both related to hazardous alcohol and drinking harms via emotional disorder symptoms and, in turn, coping drinking motives. All indirect pathways incorporating both mediators were statistically significant, and additional evidence of partial specificity was found. Conclusions/Importance: The study's results have important implications for personality-matched interventions for addictive disorders.
Article
Full-text available
We present a revision of the 1978 reformulated theory of helplessness and depression and call it the hopelessness theory of depression. Although the 1978 reformulation has generated a vast amount of empirical work on depression over the past 10 years and recently has been evaluated as a model of depression, we do not think that it presents a clearly articulated theory of depression. We build on the skeletal logic of the 1978 statement and (a) propose a hypothesized subtype of depression— hopelessness depression, (b) introduce hopelessness as a proximal sufficient cause of the symptoms of hopelessness depression, (c) deemphasize causal attributions because inferred negative consequences and inferred negative characteristics about the self are also postulated to contribute to the formation of hopelessness and, in turn, the symptoms of hopelessness depression, and (d) clarify the diathesis—stress and causal mediation components implied, but not explicitly articulated, in the 1978 statement. We report promising findings for the hopelessness theory and outline the aspects that still need to be tested. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Article
Full-text available
Background: Personality-targeted cognitive-behavioural interventions have been proven to be effective in reducing alcohol-related behaviours in adolescents. Aims: As these interventions target personality traits linked to risk for non-addictive psychopathology, the aim of this study is to examine the extent to which this approach can also prevent the onset or reduce relevant psychological problems in youth. Method: Participants aged 13 – 16 years (n = 423) were randomly assigned to either a personality matched cognitive-behavioural intervention or a no-intervention control. The personality matched interventions targeted four personality risk factors: negative thinking (NT), anxiety sensitivity (AS), impulsivity (IMP), and sensation seeking (SS). Results: Baseline and follow-up data were obtained on depression scores, panic attacks, and reckless behaviour. Results showed a moderate effect of the NT intervention on depression scores, and a similar effect of the AS intervention on panic attack and truancy (i.e., school avoidance). A small but significant intervention effect was found for shoplifting for the entire sample, as well as a moderate intervention effect on this outcome for the IMP intervention group. Conclusions: These intervention effects indicate that personality-targeted interventions designed to prevent alcohol misuse, can concurrently reduce other relevant psychological problems in youth.
Article
Full-text available
The first part of this article describes a study of the relationships between personality and risk-taking in six areas: smoking, drinking, drugs, sex, driving, and gambling. The participants, 260 college students, were given self-report measures of risky behaviors in each of the six areas and the Zuckerman- Kuhlman five-factor personality questionnaire. Generalized risk-taking (across all six areas) was related to scales for impulsive sensation seeking, aggression, and sociability, but not to scales for neuroticism or activity. Gender differences on risk-taking were mediated by differences on impulsive sensation seeking. The second part discusses biological traits associated with both risk-taking and personality, particularly sensation seeking, such as the D4 dopamine receptor gene, the enzyme monoamine oxidase, and augmenting or reducing of the cortical evoked potential. Comparative studies show relationships between biological markers shared with other species and correlated behaviors similar to sensation seeking in humans. A biosocial model of the traits underlying risk-taking is presented.
Article
The development of questionnaire scales to measure sensation seeking, first as a general trait and then as one with two or four facets, is described. Behavioral correlates of the trait include: volunteering for unusual or risky experiences, exceptional dangerous sports, fast and reckless driving, variety of sexual partners and activities, smoking, drinking and drugs, and risky or stressful vocations. Sensation seeking also influences preferences in art, media, music, movies, and television with a preference for novel, intense, and arousing themes like sex and violence.
Article
The Substance Use Risk Profile Scale (SURPS) is based on a model of personality risk for substance abuse in which four personality dimensions (hopelessness, anxiety sensitivity, impulsivity, and sensation seeking) are hypothesized to differentially relate to specific patterns of substance use. The current series of studies is a preliminary exploration of the psychometric properties of the SURPS in two populations (undergraduate and high school students). In study 1, an analysis of the internal structure of two versions of the SURPS shows that the abbreviated version best reflects the 4-factor structure. Concurrent, discriminant, and incremental validity of the SURPS is supported by convergent/divergent relationships between the SURPS subscales and other theoretically relevant personality and drug use criterion measures. In Study 2, the factorial structure of the SURPS is confirmed and evidence is provided for its test–retest reliability and validity with respect to measuring personality vulnerability to reinforcement-specific substance use patterns. In Study 3, the SURPS was administered in a more youthful population to test its sensitivity in identifying younger problematic drinkers. The results from the current series of studies demonstrate support for the reliability and construct validity of the SURPS, and suggest that four personality dimensions may be linked to substance-related behavior through different reinforcement processes. This brief assessment tool may have important implications for clinicians and future research.
Chapter
This chapter discusses how persuasive messages with novel components can attract and hold the attention of sensation seekers (SS) and bring about significant behavior changes in them. A host of genetic research works in humans indicate that vulnerability to drug abuse is heritable. Most work in this area is based on data collected from alcoholics. Given the relation between sensation seeking and drug use among adolescents, it would be valuable to understand the basic neurogenetic mechanisms that may underlie this relation. One simple hypothesis that can be offered is that high SS differ from low SS in their response to drugs due to differences in the biological mechanisms involved in drug reward. There are preliminary results from a follow-up study involving nearly 3000 students in rural Kentucky high schools. A similar design was employed, in which schools were assigned to Reducing the Risk, Modified Reducing the Risk, and a comparison condition employing the schools' standard, non-skills-based curriculum.