Abstract
Introduction
Methamphetamine (MA) users report higher levels of impulsivity relative to healthy controls, which may either result from, or precede, their substance use. Further, there is evidence that female MA users may be more impulsive than male MA users prior to MA use. Thus, the goal of the current study was to determine whether different subtraits of self-reported impulsivity are significantly related to age at first MA use, controlling for total years of MA use.
Methods
A community sample of MA users was recruited for this study (N = 157; 113 males, 44 females). The Barratt Impulsiveness Scale (BIS-11) was used to assess self-reported impulsivity on three subscales (Attentional, Motor, Non-planning). Age at first MA use served as the dependent variable in a series of multiple regression models with BIS-11 subscales, sex, and their interaction as independent variables, controlling for total years of MA use.
Results
Attentional and Motor impulsivity were significantly related to age at first MA use when controlling for total years of MA use (Attentional: p = 0.008; Motor: p = 0.003).
Conclusions
Individuals who reported higher Attentional and Motor impulsivity started using MA at an earlier age, which could suggest that impulsivity levels may be an important marker of vulnerability towards MA use. These findings indicate that prevention efforts may be targeted towards individuals who report high levels of Attentional and Motor impulsivity, as they may be at greatest risk for earlier initiation of MA use.
Keywords: Impulsivity, Methamphetamine, Age, Initiation, Attention, Motor
1. Introduction
Methamphetamine (MA) use has been associated with serious psychiatric and medical health issues at the individual level and is highly costly to society (for reviews see Courtney &Ray, 2014; Rawson, 2014). According to the Monitoring the Future Survey (Johnston, O'Malley, Meich, Bachman, & Schulenberg, 2016), approximately 1% of 12th graders report MA use in their lifetime, which increases to 6.2% (Center for Behavioral Health: Statistics and Quality, 2015) by the time individuals are age 26 or older. First use of MA occurs at about 22 years of age (Center for Behavioral Health: Statistics and Quality, 2015), during the transition between late adolescence and emerging adulthood. While many factors may be associated with the initiation and maintenance of MA use, impulsivity is a personality trait found to be higher in MA users relative to healthy controls (Ballard, et al., 2015; Ellis, et al., 2016; Hoffman, et al., 2006).
Impulsivity is considered to be a multidimensional personality trait in which individuals have an urge to perform a goal-directed behavior in pursuit of a reward; different forms of impulsivity may include lack of inhibition, risky decision making, and delay discounting (for review see Jentsch et al., 2014). For example, MA dependent individuals are more likely to select small immediate rewards relative to larger delayed rewards on a delay discounting task compared with controls (Ballard, et al., 2015; Hoffman, et al., 2006). They also display deficits in inhibiting pre-potent responses indicated by longer stop-signal reaction times on the Stop-Signal Task (Monterosso, Aron, Cordova, Xu, & London, 2005) relative to healthy controls. These objective measures of impulsivity suggest MA users have difficulties in multiple domains of impulsivity, including those involving impulsive choice (i.e. delay discounting), and those involving impulsive action (i.e. motor impulsivity; Grant & Chamberlain, 2014).
Furthermore, when subjectively assessing impulsivity, MA users cite impulsivity as the second highest reason for using MA, following the pleasurable effects they experience from using the drug (Newton, De La Garza, Kalechstein, Tziortzis, & Jacobsen, 2009). A recent study supports this finding, as not only were treatment-seeking MA dependent individuals less behaviorally inhibited on objective measures of impulsivity, but they also had higher levels of subjective impulsivity relative to controls (Ellis, et al., 2016). A common measure used to assess subjective impulsivity is the Barratt Impulsiveness Scale (BIS-11), which has been divided into three second-order factors, including Attentional, Motor, and Non-planning impulsiveness (Patton, Stanford, & Barratt, 1995). Attentional impulsiveness has been defined as “an inability to focus attention or concentrate”, Motor impulsiveness has been characterized as “as acting without thinking”, while Non-planning impulsiveness has been conceptualized as a “lack of futuring or forethought” (Stanford, et al., 2009). Understanding which of these components of impulsivity may be related to MA use would allow for more targeted intervention programs focused on improving specific subtraits of inhibitory control.
Sex differences in impulsivity and its subtraits may also be present in MA users, such that lack of behavioral inhibition in females, as assessed by retrospective reporting, could render them more vulnerable to engaging in MA use (Winhusen & Lewis, 2013). Additionally, a recent neuroimaging study examining sex differences in impulsivity and brain structure in MA users reported that age at first MA use was significantly negatively related to Behavioral impulsivity in female MA users, while this relationship was not present in male MA users (Kogachi, Chang, Alicata, Cunningham, & Ernst, 2016). Furthermore, in other stimulant users, such as those using crack/cocaine, female users were more impulsive than male users, and impulsivity served as a risk factor for the relationship between gender and crack/cocaine dependence (Lejuez, Bornovalova, Reynolds, Daughters, & Curtin, 2007). Finally, beyond behavioral inhibition, decision making deficits have been shown to be greater in female cocaine and MA users than male users of these substances (van der Plas, Crone, van den Wildenberg, Tranel, & Bechara, 2009), suggesting that executive functioning deficits may be present to a greater extent in female relative to male MA users.
1.1 Current study
It remains unclear whether higher impulsivity is a premorbid risk factor for initiating MA use or if heightened impulsivity is largely a consequence of MA use (Grant & Chamberlain, 2014). The current study of non-treatment seeking MA users expands upon recently reported findings (Kogachi, et al., 2016) by examining the relationships between Attentional, Motor, and Non-planning subtraits of impulsivity and age at first MA use, while accounting for number of years of MA use in a sample of non-abstinent MA users over twice as large as previously investigated (Kogachi, et al., 2016). The current study will help clarify the types of behavioral disinhibition that may be related to early initiation of MA use and whether sex and sex-by-impulsivity interactions are associated with age at first MA use. While, previous reports suggest objectively measured impulsivity in MA users is not associated with years of MA use (Ballard, et al., 2015; Hoffman, et al., 2006; Monterosso, et al., 2005), it is unclear whether self-reported impulsivity could be related to chronicity of MA use, making it an important covariate for the current analyses.
We hypothesized that higher self-reported Motor impulsivity in MA users (Monterosso, et al., 2005) would be associated with earlier initiation of MA use, controlling for total years of MA use. Further, we hypothesized that this effect would be more pronounced in female MA users relative to male MA users (Kogachi, et al., 2016). By examining age of first use, this study investigates whether impulsivity may be associated with MA use initiation in a primarily MA-using community sample.
2. Material and methods
2.1. Participant recruitment and exclusionary criteria
A community sample of non-treatment seeking MA users (N = 203) was recruited through online and print advertisements as part of a medication study (Ray, et al., 2015). As part of the parent behavioral pharmacology study, participants were included in the study if they were between 18–50 years old (to ensure a healthy sample without confounds of aging associated medical conditions), fluent in English, and reported using MA in the past month. Exclusionary criteria at the initial phone screening (N = 984) for the study included 1) major psychiatric disorders, including major depressive disorder with suicidal ideation, or psychotic disorders such as bipolar I and schizophrenia, 2) any other current self-reported substance use in order to recruit a primarily MA as opposed to polysubstance-using sample (excluding alcohol, tetrahydrocannabinol (THC), or nicotine), 3) currently seeking or in treatment for MA use (in order to avoid confounds with medication aim of the study), 4) presence/treatment of major medical conditions (to enroll a medically healthy sample of participants) and 5) use of medications contraindicated for the behavioral pharmacology study (Ray, et al., 2015). Furthermore, exclusionary criteria for the current analyses were the following, 1) absence of urine toxicology test (N = 8), 2) positive urine toxicology test for any substance other than MA or THC (N = 10), 3) missing data for age at first MA use (N = 5), and 4) incomplete data on the Barratt Impulsiveness Scale [BIS-11 (Patton, et al., 1995); N = 23)]. Following the implementation of the exclusionary criteria described above, 157 (113 males/44 females) participants were included in the final analyses for the current study. All study procedures were approved by the University of California, Los Angeles Institutional Review Board and were in accordance with the Declaration of Helsinki.
2.2. Study measures
The Structured Clinical Interview for DSM-IV Disorders (SCID-IV) was used to assess whether participants met criteria for MA abuse and/or dependence and asked participants to report their age at first MA use. Total years of MA use was calculated by subtracting age at first MA use from age at the time of study participation. The Timeline Followback (TLFB) calendar-assisted interview (Sobell & Sobell, 1992) asked participants to recall the amount of MA (in grams) they used in the past 30 days. Participants completed one of the most commonly used self-report measures of impulsivity, the 30-item BIS-11 (Patton, et al., 1995; Stanford, et al., 2009). Items were scored and divided into three different second-order subscales, including Attentional, Motor, and Non-planning impulsivity, and a total impulsivity score was calculated. Participants read each of the statements on the questionnaire and responded on a scale of 1 = Rarely/Never to 4 = Almost Always/Always, as to whether the statement applied to them. Sample items from the subscales include “I often have extraneous thoughts when thinking” (Attentional), “I act on the spur of the moment” (Motor), and “I am more interested in the present than the future” (Non-planning). While not correlated with behavioral measures of impulsivity, all subscales have been shown to highly correlate with other self-report measures of impulsivity (Stanford, et al., 2009). Internal consistency (Chronbach’s α) for the BIS-11 total score and subscales has been reported to be: Total: 0.83, Attentional: 0.74, Motor: 0.59, Non-planning: 0.72, while test-retest reliability (Spearman’s ρ) are as follows: Total: 0.83, Attentional: 0.61, Motor: 0.67, Non-planning: 0.72 (Stanford, et al., 2009).
2.3. Statistical analyses
Statistical analyses were conducted in IBM SPSS (Version 22.0). Three hierarchical multiple linear regressions were examined to investigate the relationship of self-reported impulsivity on each of the BIS-11 subscales with age at first MA use. First, total years of MA use was entered into the model, followed by the self-reported impulsivity score on one of the three subscales, sex, and the sex-by-impulsivity interaction term. Thus, each hierarchical multiple regression (i.e., testing each BIS subscale separately) examined whether self-reported impulsivity, sex, and/or their interaction were significantly (p < 0.05) associated with age at first MA use after accounting for total years of MA use.
3. Results
Demographic characteristics for the current study sample are presented in Table 1. On average, participants in the current study were in their mid-30’s, started using MA in their early 20’s, had a mean total BIS-11 score of 67.6±13.3, and the majority of the sample (N = 137) met past month DSM-IV dependence for MA. There was a significantly greater proportion of females who reported being White than males (p = 0.02). The number of male MA users who met DSM-IV criteria for MA abuse was proportionately greater than the number of female MA users who met DSM-IV criteria for MA abuse at a trend level (p = 0.06). There was also a trend, such that females reported greater total impulsivity on the BIS-11 than males (p = 0.07). This appeared to be driven by significantly greater Non-planning impulsivity reported by females relative to males (p = 0.04), and there was a trend for females to report greater Attentional impulsivity compared with males (p = 0.08).
Table 1.
Demographics, Substance Use Characteristics, and BIS Impulsivity Scores of Methamphetamine Users.
Total | Females | Males | t, U, X2 | p | |
---|---|---|---|---|---|
Age | 35.0(8.6) | 35.3(9.7) | 34.9(8.2) | −0.22 | 0.83 |
Sex (N) | 157 | 44 | 113 | ||
Ethnicitya | |||||
White | 63 | 24 | 39 | 5.29 | 0.02 |
Black | 40 | 8 | 32 | 1.71 | 0.19 |
Asian | 6 | 1 | 5 | 0.40 | 0.53 |
Latino | 59 | 15 | 44 | 0.32 | 0.57 |
Native American | 4 | 1 | 3 | 0.02 | 0.89 |
Past month MA dependence (N)b | 137 | 40 | 97 | 0.55 | 0.46 |
Past month MA abuse (N)b | 116 | 28 | 88 | 3.70 | 0.06 |
Age at first MA use | 22.7(7.7) | 21.8(6.9) | 23.0(7.9) | 0.88 | 0.38 |
Years of MA use | 12.3(8.6) | 13.4(9.7) | 11.9(8.1) | −1.0 | 0.32 |
Grams of MA use (in past 30 days)c | 19.0(32.9) | 18.4(25.5) | 19.2(35.6) | 0.13 | 0.89 |
Smoking Frequency (Daily/Occasionally/Not at All) | 83/24/50 | 25/5/14 | 58/19/36 | 0.80 | 0.67 |
Alcohol Use Frequencyb | 3.84 | 0.43 | |||
Never | 31 | 10 | 21 | ||
Monthly or less | 57 | 19 | 38 | ||
2–4 times a month | 26 | 5 | 21 | ||
2–3 times a week | 24 | 4 | 20 | ||
4 or more times a week | 18 | 6 | 12 | ||
Marijuana Smoker (Yes/No)b | 70/86 | 15/29 | 55/57 | 2.88 | 0.09 |
BIS-11 Total | 67.6(13.3) | 70.7(12.4) | 66.4(13.2) | −1.84 | 0.07 |
BIS-11 Attentional | 16.4(4.7) | 17.5(4.3) | 16.0(4.7) | −1.78 | 0.08 |
BIS-11 Motor | 24.4(5.5) | 25.0(5.8) | 24.1(5.3) | −0.99 | 0.32 |
BIS-11 Non-planning | 26.9(5.6) | 28.2(4.8) | 26.3(5.8) | −1.88 | 0.04 |
Mean (standard deviation) unless otherwise noted. Bold p values indicate significant group differences between males and females.
Participants may have indicated multiple ethnicities.
Missing for one participant.
Missing for 7 males and 1 female.
All three impulsivity subscales were highly correlated with one another: Motor-Attention (r = 0.61, p < 0.001), Attention-Non-planning (r = 0.57, p < 0.001), and Motor-Non-planning (r = 0.51, p < 0.001). The Cronbach’s α coefficient for the total BIS scale was good (0.87), and acceptable for each of the three subscales (Attention = 0.74, Motor = 0.74, Non-planning = 0.73). There was a significant positive relationship between the total impulsivity score on the BIS-11 and total years of MA use, in the entire sample (r = 0.30, p < 0.001), and in males alone (r = 0.39, p < 0.0001), but not in females (r = 0.08, p = 0.63). Impulsivity subscales were significantly correlated with total years of MA use in the overall sample (Attentional: r = 0.23, p = 0.004; Motor: r = 0.07, p = 0.03; Non-planning: r = 0.36, p < 0.001), in males separately (Attentional: r = 0.29, p = 0.002; Motor: r = 0.28, p = 0.003; Non-planning: r = 0.42, p < 0.001), but not in females (Attentional: r = 0.07, p = 0.67, Motor: r = −.05, p = 0.74; Non-planning: r = 0.20, p = 0.20). There was no significant correlation between number of grams of MA used in the past 30 days and the total BIS-11 impulsivity score in the entire sample (r = −.09, p = 0.26), or in males (r = −0.11, p = 0.26), or females (r = −0.03, p = 0.86), separately.
The results of the regression models indicated that Attentional and Motor impulsivity were both significantly associated with age at first MA use [Attentional (Table 2A): ΔR2 = 0.05, β = −.23, t = −2.69, p = 0.008, Cohens f2 = 0.07, Power (1-β) = 0.77; Motor (Table 2B): ΔR2 = 0.05, β = −.27, t = −3.06, p = 0.003; Cohens f2 = 0.07, Power (1-β) = 0.80] after accounting for total years of MA use (Figure 1; Table 2), while there were no significant effects of sex and no sex-by-impulsivity interactions (all p’s > 0.10). When all three impulsivity subtraits were examined within one model, Motor impulsivity was significantly related to age at first MA use (Motor: ΔR2 = 0.05, β = −.23, t = −2.01, p = 0.046, Cohen’s f2 = 0.11, Power (1-β) = 0.85) after accounting for total years of MA use (Table 3).
Table 2.
Effects of Attentional and Motor Impulsivity, Sex, and their Interaction on Age at First Methamphetamine Use
A) Attentional Impulsivity | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
Coefficientsa | |||||||||||
Model | Unstandardized Coefficients | Standardized Coefficients |
t | Sig. | 95.0% Confidence Interval for B | Correlations | |||||
B | Std. Error | Beta | Lower Bound | Upper Bound | Zero- order |
Partial | Part | ||||
1 | (Constant) | 22.682 | .550 | 41.246 | .000 | 21.595 | 23.768 | ||||
Centered_YearsMAUse | −.394 | .064 | −.442 | −6.129 | .000 | −.521 | −.267 | −.442 | −.442 | −.442 | |
2 | (Constant) | 22.717 | .638 | 35.614 | .000 | 21.457 | 23.977 | ||||
Centered_YearsMAUse | −.348 | .065 | −.390 | −5.349 | .000 | −.476 | −.219 | −.442 | −.398 | −.378 | |
Sex | −.164 | 1.230 | −.010 | −.134 | .894 | −2.594 | 2.265 | −.071 | −.011 | −.009 | |
Centered_BIS_Attention | −.371 | .138 | −.226 | −2.685 | .008 | −.645 | −.098 | −.311 | −.213 | −.190 | |
Centered_BIS_Attention_Sex | .037 | .275 | .011 | .134 | .893 | −.506 | .580 | −.126 | .011 | .009 |
B) Motor Impulsivity | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
Coefficientsa | |||||||||||
Model | Unstandardized Coefficients | Standardized Coefficients |
t | Sig. | 95.0% Confidence Interval for B | Correlations | |||||
B | Std. Error | Beta | Lower Bound | Upper Bound | Zero-order | Partial | Part | ||||
1 | (Constant) | 22.682 | .550 | 41.246 | .000 | 21.595 | 23.768 | ||||
Centered_YearsMAUse | −.394 | .064 | −.442 | −6.129 | .000 | −.521 | −.267 | −.442 | −.442 | −.442 | |
2 | (Constant) | 22.767 | .633 | 35.955 | .000 | 21.516 | 24.018 | ||||
Centered_YearsMAUse | −.350 | .065 | −.393 | −5.429 | .000 | −.478 | −.223 | −.442 | −.403 | −.381 | |
Sex | −.419 | 1.204 | −.025 | −.348 | .728 | −2.799 | 1.960 | −.071 | −.028 | −.024 | |
Centered_BIS_Motor | −.372 | .122 | −.267 | −3.056 | .003 | −.613 | −.132 | −.298 | −.241 | −.215 | |
Centered_BIS_Motor_Sex | .166 | .215 | .067 | .773 | .441 | −.258 | .590 | −.077 | .063 | .054 |
Dependent Variable: Age of first meth use
Table 3.
Effects of Self−reported Impulsivity Subtraits, Sex, and their Interaction on Age at First Methamphetamine Use
Coefficientsa | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
Model | Unstandardized Coefficients | Standardized Coefficients |
t | Sig. | 95.0% Confidence Interval for B | Correlations | |||||
B | Std. Error | Beta | Lower Bound | Upper Bound | Zero- order |
Partial | Part | ||||
1 | (Constant) | 22.682 | .550 | 41.246 | .000 | 21.595 | 23.768 | ||||
Centered_YearsMAUse | −.394 | .064 | −.442 | −6.129 | .000 | −.521 | −.267 | −.442 | −.442 | −.442 | |
2 | (Constant) | 22.764 | .634 | 35.930 | .000 | 21.512 | 24.016 | ||||
Centered_YearsMAUse | −.371 | .068 | −.416 | −5.482 | .000 | −.505 | −.237 | −.442 | −.411 | −.384 | |
Sex | −.406 | 1.230 | −.024 | −.330 | .742 | −2.837 | 2.025 | −.071 | −.027 | −.023 | |
Centered_BIS_Attention | −.237 | .185 | −.144 | −1.283 | .201 | −.602 | .128 | −.311 | −.105 | −.090 | |
Centered_BIS_Attention_Sex | −.240 | .374 | −.073 | −.641 | .522 | −.979 | .499 | −.126 | −.053 | −.045 | |
Centered_BIS_Motor | −.325 | .161 | −.232 | −2.010 | .046 | −.644 | −.006 | −.298 | −.163 | −.141 | |
Centered_BIS_Motor_Sex | .149 | .265 | .060 | .564 | .574 | −.374 | .673 | −.077 | .046 | .039 | |
Centered_BIS_Nonplanning | .171 | .137 | .126 | 1.248 | .214 | −.100 | .443 | −.206 | .102 | .087 | |
Centered_BIS_Nonplanning_Sex | .194 | .317 | .066 | .614 | .540 | −.431 | .820 | −.068 | .050 | .043 |
Dependent Variable: Age of first meth use
4. Discussion
The goal of the current study was to understand the association of self-reported impulsivity in non-treatment seeking MA users with age at first MA use. These analyses serve to clarify to what extent impulsivity may be related to age at first MA use as previous studies have suggested that impulsive personality may be a risk factor for initiating or continuing to use MA (Grant & Chamberlain, 2014; Kogachi, et al., 2016; Newton, et al., 2009; Winhusen & Lewis, 2013). Furthermore, sex and sex-by-impulsivity interactions were investigated as previous research has indicated sex differences in MA use, with greater premorbid disinhibition in female MA users relative to male users (Winhusen & Lewis, 2013), and greater Behavioral impulsivity in females who initiated MA use at younger ages (Kogachi, et al., 2016). Self-reported Attentional and Motor impulsivity were significantly related to age at first MA use in current MA users, even when controlling for total years of MA use. However, there were no main effects of sex or sex-by-impulsivity interactions significantly related to age at first MA use.
The current findings suggest that individuals reporting greater problems with attentional and motor control were more likely to start using MA at an earlier age. Specifically, individuals, who currently rate themselves higher on restlessness, inability concentrating, and acting quickly without thinking, started using MA earlier in the current study relative to those participants who scored lower on these impulsivity subtraits. While MA is known to affect the dopaminergic system (for review see Yu, Zhu, Shen, Bai, & Di, 2015) and produces neurobiological alterations in this system in chronic MA users (Wilson, et al., 1996), impulsive personality characteristics may also increase vulnerability for MA use. Impulsive personality has been linked with alterations in dopaminergic activity (Weiland, et al., 2014) and dopamine receptor availability (Caravaggio, et al., 2016), and amphetamines are often prescribed to mitigate symptoms of inattention and motor disinhibition (Chan, Fogler, & Hammerness, 2016). One hypothesis is that use of MA may be a form of self-medication (Van Meer, 2014), which could manage or control symptoms of impulsivity. However, greater impulse control issues associated with aberrant dopaminergic function during adolescence and young adulthood could also be related to earlier engagement with psychostimulants, such as MA. For example, the orbitofrontal cortex and anterior cingulate cortex have been shown to underlie impulsive action, such as disinhibition and lack of motor control in preclinical studies (Jentsch, et al., 2014), suggesting neurobiological alterations in these areas may be present prior to the initiation of MA use. It should be recognized that premorbid neural markers related to impulsivity may be moderated by other risk factors for adolescent/young adult substance use, such as drug availability and peer substance use, which are also related to MA use (Embry, Hankins, Biglan, & Boles, 2009; Russell, et al., 2008; Wood, et al., 2008). Furthermore, the current findings are supported in part by a cross-sectional study examining impulsivity as an endophenotype, in which the authors found that siblings of stimulant users also had higher levels of self-reported impulsivity on the BIS-11 relative to controls, suggesting this trait may be both a risk endophenotype present in non-drug users and a personality trait related to stimulant use (Ersche, Turton, Pradhan, Bullmore, &Robbins, 2010). However, these findings were specific to the Non-planning subscale of the BIS-11, but it is possible differences in sample characteristics or sample size may have precluded the detection of significant differences on the other subscales.
The nonsignificant effects of sex or the sex-by-impulsivity interactions were surprising given past research that has noted earlier age at first MA use in females (Dluzen & Liu, 2008) and greater behavioral impulsivity in females that was significantly related to their onset of MA use (Kogachi, et al., 2016). Sample characteristics between the current and previous studies may explain some these differences. For example, in the current sample of participants there was a trend for more males relative to females to meet MA abuse criteria. Thus, overall the males in the sample may have been more severe users than the females, which is contrary to previous findings (Dluzen & Liu, 2008). Perhaps a sample of more severe female MA users would have resulted in the expected sex differences and interaction.
4.1. Limitations
While the current study has several strengths, including the examination of different forms of self-reported impulsivity as they relate to age at first MA use using the well-validated BIS-11 scale, there are limitations that should be noted. First, the parent behavioral pharmacology arm of the study necessitated the recruitment of primarily MA-using as opposed to polysubstance-using individuals, and other exclusionary criteria, such as major psychiatric conditions, used to recruit a medically healthy sample of participants, may limit generalizability of the findings. Second, the sample size was modest, but small-to-medium effects were detected for the significant findings, with power analyses suggesting high power for the Motor impulsivity regression and slightly less than ideal power for the Attentional impulsivity regression. Other factors that may explain additional variance associated with initiating MA use will need to be investigated, and a more equal sample of males and females would be preferred in future studies. Third, only past 30 day use of MA was available for the current participants. While most participants met past month DSM-IV criteria for MA dependence, we cannot ascertain that all participants had been using MA regularly since initiating use. Fourth, it is important to note that many other factors may be associated with initiation of MA use, beyond impulsivity. Drug availability, childhood psychopathology, family history of substance use disorders, lack of parental monitoring, peer substance use, risky sex, antisocial behavior, and genetic variants are some of the many factors that have been associated with MA use (Bousman, Glatt, Everall, & Tsuang, 2009; Embry, et al., 2009; Russell, et al., 2008; Wood, et al., 2008). Longitudinal studies of adolescents and young adults who initiate MA use will be able to clarify which of these risk factors may best explain age at first MA use. Furthermore, future studies should investigate the reasons for initiating MA use at different ages, as the current study suggests there is a wide age range at which individuals first start using MA. It is likely that the factors related to age at first use of MA differ for adolescents and older adults. For example, changing financial, social, and employment obligations may be more relevant to MA use initiation at older vs. younger ages. Finally, given the cross-sectional design of the study based on retrospective reporting, we cannot conclude that higher impulsivity contributed to earlier initiation of MA use, only that this association was present.
4.2. Future directions
Since average age at first MA use is about 22 (Center for Behavioral Health: Statistics and Quality, 2015), which closely matches the mean age at first MA use in the current study, impulsivity may need to be carefully examined in late adolescence and early adulthood as a risk factor for starting to use MA. While self-reported impulsivity generally shows a linear decline from childhood to adulthood (Steinberg, et al., 2008), those individuals whose impulsivity levels remain high across adolescence or whose impulsivity shows a different developmental pattern, might be the greatest risk group for adolescent or early adult MA use initiation. Future longitudinal studies focused on substance use in the late adolescent and early adulthood period should examine subjective and objective impulsivity measures as potential vulnerability markers for using MA. These studies may inform prevention efforts aimed at reducing the number of substance users who begin using psychostimulants during adolescence and young adulthood. For example, the current findings indicate that future studies may benefit from assessing different subtraits of impulsivity in high-risk adolescents. Designing interventions that reduce acting on impulse or developing tasks that increase focus and concentration in highly impulsive youth may help prevent the onset of early MA use initiation.
5. Conclusions
The current findings indicate self-reported Attentional and Motor impulsivity are significantly negatively related to age at first MA use. These results suggest that impulsive personality should be closely examined during adolescence and young adulthood when most MA use is initiated. While impulsivity may increase as a result of MA use, impairments in attentional and motor control could be early markers that indicate risk for initiating MA use. Longitudinal studies of adolescent substance users should examine whether impulsive personality, using both subjective and objective measures, predicts the initiation of MA use during late adolescence and emerging adulthood.
Highlights.
Impulsivity may be a risk factor for and a consequence of methamphetamine (MA) use.
Attentional and motor impulsivity are negatively related to age at first MA use.
Impulsivity should be examined as a risk factor for earlier onset of MA use.
Acknowledgments
Role of Funding Sources: Funding for this study was provided by the National Institute on Drug Abuse (NIDA): R21 DA029831, PI: Ray; T32 DA024635, PI: London. NIDA did not have a role in the study design, collection, analysis or interpretation of the data, writing of the manuscript, or the decision to submit the manuscript for publication.
Footnotes
Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Contributors: AC and LAR designed the study. AC conducted statistical analyses and wrote the first draft of the manuscript. Both AC and LR have contributed to and approved the final version of the manuscript.
Conflict of Interest: LAR is a paid consultant for GSK and has received study medication from Pfizer and Medicinova.
References
- Ballard ME, Mandelkern MA, Monterosso JR, Hsu E, Robertson CL, Ishibashi K, Dean AC, London ED. Low Dopamine D2/D3 Receptor Availability is Associated with Steep Discounting of Delayed Rewards in Methamphetamine Dependence. Int J Neuropsychopharmacol. 2015;18 doi: 10.1093/ijnp/pyu119. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Bousman CA, Glatt SJ, Everall IP, Tsuang MT. Genetic association studies of methamphetamine use disorders: A systematic review and synthesis. Am J Med Genet B Neuropsychiatr Genet. 2009;150B:1025–1049. doi: 10.1002/ajmg.b.30936. [DOI] [PubMed] [Google Scholar]
- Caravaggio F, Fervaha G, Chung JK, Gerretsen P, Nakajima S, Plitman E, Iwata Y, Wilson A, Graff-Guerrero A. Exploring personality traits related to dopamine D2/3 receptor availability in striatal subregions of humans. Eur Neuropsychopharmacol. 2016;26:644–652. doi: 10.1016/j.euroneuro.2016.02.010. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Chan E, Fogler JM, Hammerness PG. Treatment of Attention-Deficit/Hyperactivity Disorder in Adolescents: A Systematic Review. Jama. 2016;315:1997–2008. doi: 10.1001/jama.2016.5453. [DOI] [PubMed] [Google Scholar]
- Courtney KE, Ray LA. Methamphetamine: an update on epidemiology, pharmacology, clinical phenomenology, and treatment literature. Drug Alcohol Depend. 2014;143:11–21. doi: 10.1016/j.drugalcdep.2014.08.003. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Dluzen DE, Liu B. Gender differences in methamphetamine use and responses: a review. Gend Med. 2008;5:24–35. doi: 10.1016/s1550-8579(08)80005-8. [DOI] [PubMed] [Google Scholar]
- Ellis C, Hoffman W, Jaehnert S, Plagge J, Loftis JM, Schwartz D, Huckans M. Everyday problems with executive dysfunction and impulsivity in adults recovering from methamphetamine addiction. Addict Disord Their Treat. 2016;15:1–5. doi: 10.1097/ADT.0000000000000059. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Embry D, Hankins M, Biglan A, Boles S. Behavioral and social correlates of methamphetamine use in a population-based sample of early and later adolescents. Addict Behav. 2009;34:343–351. doi: 10.1016/j.addbeh.2008.11.019. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Ersche KD, Turton AJ, Pradhan S, Bullmore ET, Robbins TW. Drug addiction endophenotypes: impulsive versus sensation-seeking personality traits. Biol Psychiatry. 2010;68:770–773. doi: 10.1016/j.biopsych.2010.06.015. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Grant JE, Chamberlain SR. Impulsive action and impulsive choice across substance and behavioral addictions: cause or consequence? Addict Behav. 2014;39:1632–1639. doi: 10.1016/j.addbeh.2014.04.022. [DOI] [PubMed] [Google Scholar]
- Hoffman WF, Moore M, Templin R, McFarland B, Hitzemann RJ, Mitchell SH. Neuropsychological function and delay discounting in methamphetamine-dependent individuals. Psychopharmacology (Berl) 2006;188:162–170. doi: 10.1007/s00213-006-0494-0. [DOI] [PubMed] [Google Scholar]
- Jentsch JD, Ashenhurst JR, Cervantes MC, Groman SM, James AS, Pennington ZT. Dissecting impulsivity and its relationships to drug addictions. Ann N Y Acad Sci. 2014;1327:1–26. doi: 10.1111/nyas.12388. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Johnston LD, O'Malley PM, Meich RA, Bachman JG, Schulenberg JE. Monitoring the Future: National survey results on drug use, 1975–2015: Overview, key findings on adolescent drug use. Ann Arbor: Institute for Social Research, University of Michigan; 2016. [Google Scholar]
- Kogachi S, Chang L, Alicata D, Cunningham E, Ernst T. Sex differences in impulsivity and brain morphometry in methamphetamine users. Brain Struct Funct. 2016 doi: 10.1007/s00429-016-1212-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Lejuez CW, Bornovalova MA, Reynolds EK, Daughters SB, Curtin JJ. Risk factors in the relationship between gender and crack/cocaine. Exp Clin Psychopharmacol. 2007;15:165–175. doi: 10.1037/1064-1297.15.2.165. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Monterosso JR, Aron AR, Cordova X, Xu J, London ED. Deficits in response inhibition associated with chronic methamphetamine abuse. Drug Alcohol Depend. 2005;79:273–277. doi: 10.1016/j.drugalcdep.2005.02.002. [DOI] [PubMed] [Google Scholar]
- Newton TF, De La Garza R, 2nd, Kalechstein AD, Tziortzis D, Jacobsen CA. Theories of addiction: methamphetamine users' explanations for continuing drug use and relapse. Am J Addict. 2009;18:294–300. doi: 10.1080/10550490902925920. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Patton JH, Stanford MS, Barratt ES. Factor structure of the Barratt impulsiveness scale. J Clin Psychol. 1995;51:768–774. doi: 10.1002/1097-4679(199511)51:6<768::aid-jclp2270510607>3.0.co;2-1. [DOI] [PubMed] [Google Scholar]
- Quality., C. f. B. H. S. a. 2014 National Survey on Drug Use and Health: Detailed Tables. Rockville, MD: Substance Abuse and Mental Health Services Administration; 2015. [Google Scholar]
- Rawson RA. Current research on the epidemiology, medical and psychiatric effects, and treatment of methamphetamine use. J Food Drug Anal. 2013;21:S77–S81. doi: 10.1016/j.jfda.2013.09.039. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Ray LA, Bujarski S, Courtney KE, Moallem NR, Lunny K, Roche D, Leventhal AM, Shoptaw S, Heinzerling K, London ED, Miotto K. The Effects of Naltrexone on Subjective Response to Methamphetamine in a Clinical Sample: a Double-Blind, Placebo-Controlled Laboratory Study. Neuropsychopharmacology. 2015 doi: 10.1038/npp.2015.83. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Russell K, Dryden DM, Liang Y, Friesen C, O'Gorman K, Durec T, Wild TC, Klassen TP. Risk factors for methamphetamine use in youth: a systematic review. BMC Pediatr. 2008;8:48. doi: 10.1186/1471-2431-8-48. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Sobell LC, Sobell MB. Timeline follow-back: A technique for assessing self-reported alcohol consumption. In: Litten & RZ, Allen J, editors. Measuring alcohol consumption: Psychological and biological methods. New Jersey: Humana Press; 1992. pp. 41–72. [Google Scholar]
- Stanford MS, Mathias CW, Dougherty DM, Lake SL, Anderson NE, Patton JH. Fifty years of the Barratt Impulsiveness Scale: An update and review. Personality and Individual Differences. 2009;47:385–395. [Google Scholar]
- Steinberg L, Albert D, Cauffman E, Banich M, Graham S, Woolard J. Age differences in sensation seeking and impulsivity as indexed by behavior and self-report: evidence for a dual systems model. Dev Psychol. 2008;44:1764–1778. doi: 10.1037/a0012955. [DOI] [PubMed] [Google Scholar]
- van der Plas EA, Crone EA, van den Wildenberg WP, Tranel D, Bechara A. Executive control deficits in substance-dependent individuals: a comparison of alcohol, cocaine, and methamphetamine and of men and women. J Clin Exp Neuropsychol. 2009;31:706–719. doi: 10.1080/13803390802484797. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Van Meer R. Stimulant substitution in methamphetamine dependence from the perspective of adult ADHD. Aust N Z J Psychiatry. 2014;48:95–96. doi: 10.1177/0004867413492221. [DOI] [PubMed] [Google Scholar]
- Weiland BJ, Heitzeg MM, Zald D, Cummiford C, Love T, Zucker RA, Zubieta JK. Relationship between impulsivity, prefrontal anticipatory activation, and striatal dopamine release during rewarded task performance. Psychiatry Res. 2014;223:244–252. doi: 10.1016/j.pscychresns.2014.05.015. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Wilson JM, Kalasinsky KS, Levey AI, Bergeron C, Reiber G, Anthony RM, Schmunk GA, Shannak K, Haycock JW, Kish SJ. Striatal dopamine nerve terminal markers in human, chronic methamphetamine users. Nat Med. 1996;2:699–703. doi: 10.1038/nm0696-699. [DOI] [PubMed] [Google Scholar]
- Winhusen T, Lewis D. Sex differences in disinhibition and its relationship to physical abuse in a sample of stimulant-dependent patients. Drug Alcohol Depend. 2013;129:158–162. doi: 10.1016/j.drugalcdep.2012.09.014. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Wood E, Stoltz JA, Zhang R, Strathdee SA, Montaner JS, Kerr T. Circumstances of first crystal methamphetamine use and initiation of injection drug use among high-risk youth. Drug Alcohol Rev. 2008;27:270–276. doi: 10.1080/09595230801914750. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Yu S, Zhu L, Shen Q, Bai X, Di X. Recent advances in methamphetamine neurotoxicity mechanisms and its molecular pathophysiology. Behav Neurol. 2015;2015:103969. doi: 10.1155/2015/103969. [DOI] [PMC free article] [PubMed] [Google Scholar]