Group Discussion

sensitive home environments exhibit heightened levels of regu- latory competence (Brody & Flor, 1997; Deater-Deckard, 2014). Exposure to adverse and chaotic rearing environments are thought to exacerbate impulsivity through stimulation of mesolimbic pathways (Koob & Kreek, 2007) and to undermine the development of self-regulation via decrements in executive functioning (McEwen, 2008). Accordingly, environmental in- fluences such as those associated with familial experiences are central to the development of self-regulatory capacities and the attendant expression of impulsive decision making.

Recent perspective on stress and development suggest that life experiences are processed and appraised cognitively, shaping coping behaviors and accompanied by reorganiza- tion in the developing brain (Lovallo, 2013). Neurocognitive adaptations in response to adverse childhood experiences, such as child abuse and neglect, include dampened stress re- activity, a propensity to focus on short-term goals, impulsive response selection, and emotion dysregulation with a prefer- ence toward negative states; these are all factors that contrib- ute to impulsive behavior (Lovallo, 2013; Lovic, Keen, Fletcher, & Fleming, 2011). For example, reports from the Oklahoma Family Health Patterns Project found that indi- viduals with a history of adversity exhibited cognitive dysreg- ulation, including problems with delaying gratification, a core facet of impulsive decision making (Lovallo et al., 2013; Lo- vallo, Farag, Sorocco, Cohoon, & Vincent, 2012). Using an experimental design, Kidd, Palmeri, and Aslin (2013) found that environmental unreliability affected children’s delay of gratification. Similarly, a recent study documented links be- tween child maltreatment and antisocial behaviors in children via impulsivity (Thibodeau, Cicchetti, & Rogosch, 2015).

Although numerous studies have documented how aspects of impulsive behavior proximally predict substance use and abuse (Coskunpinar, Dir, & Cyders, 2013; MacKillop et al., 2011; Verdejo-Garcı́a, Lawrence, & Clark, 2008), the developmental hypothesis that impulsivity acts as mechanism linking adverse rearing environments to downstream sub- stance abuse remains to be investigated. This gap in the litera- ture has occurred in part due to the focus of addiction research on conceptualizing impulsivity as a trait (Kreek, Nielsen, Bu- telman, & LaForge, 2005), rather than a neurocognitive adap- tation to demands of the rearing environment. In the present study, we not only investigate the potential for impulsivity to act as a mechanism linking adverse childhood experience experiences to substance use but also respond to calls from re- searchers to provide more nuanced and multidimensional characterizations of impulsive decision making (Dick et al., 2010). We include an examination of impulsivity using both trait (Whiteside & Lynam, 2001) and delay discounting (Bickel & Marsch, 2001) perspectives followed by a high- resolution investigation of impulsivity effects on substance use employing a multifactorial theory of impulsive behavior.

We address these aims in two studies. Study 1 tests the in- direct influence of impulsivity in linking childhood abuse and neglect to substance use in young adulthood. This hypothesis was evaluated using a national probability sample with a lon-

gitudinal design. This study permitted a proof of principle hy- pothesis that early adversity, in the form of child abuse and neglect, would be associated prospectively with impulsive behavior in adolescence, which in turn would predict sub- stance use in young adulthood. Although large, longitudinal samples are ideal for testing broad hypotheses regarding mechanisms and provide high levels of generalizability, these samples, rarely, if ever, have fine-grained operationalization of key concepts. We thus conducted a second, cross-sectional study where we sampled 1,100 adults who completed multi- ple measures of impulsivity, assessments of their exposure to a range of adverse childhood experiences, and their current substance use. In Study 2, we investigated two perspectives on impulsivity: one using a self-report measure of impulsive behavior and the other using a task-based assessment of delay of gratification. We then conducted additional analyses of the influence of specific facets of self-reported impulsivity. We have organized the presentation of these two studies as fol- lows. We provide an introduction to Study 1, followed by its methods, results, and discussion. This is followed by a similarly structured presentation for Study 2. Below we pre- sent each study in its entirety, followed by an integrative dis- cussion of the findings across studies.

Study 1

Alcohol, cigarettes, and cannabis are the substances most commonly used by young people in the United States (Na- tional Center for Health Statistics, 2007). The primary aim of Study 1 was to evaluate the hypothesis that child abuse and neglect would predict young adult alcohol, nicotine, and cannabis use indirectly via impulsivity assessed in ado- lescence. Youth who were exposed to child abuse and neglect are expected to have “adapted” to the environment by evinc- ing a preference for short-term gratification and attendant difficulties with regulating impulsive behavior. These cognitive vulnerabilities are known proximal risk factors for substance use and abuse (Crews & Boettiger, 2009; Garavan, 2011).

In addition to our primary hypotheses, we examined the potential for sex to modulate the paths linking child abuse and neglect, impulsivity, and substance use. Sex differences in self-reported impulsivity are well documented (Cross, Copping, & Campbell, 2011). Little or no research, however, has examined the potential for sex to moderate the associa- tions among child abuse and neglect, impulsivity, and sub- stance use. Studies of other youth risk behaviors, however, suggest that sex differences may condition these paths. For example, Black, McMahon, Potenza, Fiellin, and Rosen (2015) found that the association between impulsivity and sexual risk taking was higher for males than for females. Comparable moderating effects were apparent in an investiga- tion of the links between impulsivity and health risk behavior (Stoltenberg, Batien, & Birgenheir, 2008). Although studies of sex moderation on the association between child abuse and neglect and impulsivity remain to be conducted, there is evidence that sex interacts with childhood maltreatment

A. Oshri et al.2

to predict mental health outcomes (Arnow, Blasey, Hunkeler, Lee, & Hayward, 2011; Lejuez et al., 2002). Thus, in the pres- ent study sex differences were investigated in the associations between child abuse and neglect experiences and impulsivity and between impulsivity and substance use.

Study hypotheses were tested with prospective data from National Longitudinal Study of Adolescent to Adult Health (Add Health). Given that impulsivity was measured during adolescence at Waves 2 and 3, the Add Health data provided a unique sample on which to test the proof-of-principle hy- pothesis that impulsivity would link child abuse and neglect to drug use in young adulthood. Data from young people at age 28 permitted assessment of drug use during a time period when the majority of young people have declined in their use. Thus, we were able to examine the persistence of drug use after a common developmental phase in which substance use is elevated.

Methods

Sample. Add Health is a nationally representative sample of adolescents in Grades 7–12 in the United States. Baseline data were collected in 1994–1995 from 20,745 middle and high school students from 144 schools using a stratified clus- ter-sampling method. Parents of participating students were also asked to complete questionnaires at baseline. Data were collected again in 1995–1996 (Wave 2), 2001–2002 (Wave 3), and 2007–2008 (Wave 4). For inclusion in the pres- ent study, we used data from all participants for whom Wave 4 sampling weights were calculated (n ¼ 9,421). These weights corrected for oversampling of smaller population groups and adjusted for attrition (Brownstein et al., 2011). Hypotheses were tested with data from the baseline parent questionnaire (demographics) and Waves 2–4 of the adoles- cent/young adult interview. In the analytic sample, partici-

pant mean age was 15.2 years, (SD ¼ 1.56) at baseline, 16.2 years (SD ¼ 1.63) at Wave 2, 21.2 years (SD ¼ 1.63) at Wave 3, and 28.8 years (SD ¼ 1.59) at Wave 4. The sample was 55.6% female, and the ethnic composition was Caucasian (56.6%), Hispanic (14.9%), African American (21.3%), and 7.3% Asian (7.3%). Most adolescents’ parents (75.5%) had at least a high school diploma. The median fam- ily income at baseline (1995) was $40,000. The University of Georgia Institutional Review Board approved analyses of this secondary data resource.

Measures.

Child abuse and neglect. Exposure to child abuse and ne- glect was operationalized as a latent construct using four items obtained from youth at Wave 3. The items asked the fre- quency of specific child maltreatment experiences prior to Grade 6. These experiences included supervisory neglect (“How often were you left home alone?”), physical needs ne- glect (“not taken care of basic needs”), child physical abuse (“How often . . . slapped, hit, or kicked you?”), and child sex- ual abuse (“How often . . . touched you in a sexual way . . .”). The items were scaled from 0 (never) to 5 (more than 10 times). These items have been used in previous research and are sensitive to substance use outcomes (Fang & Corso, 2007; Ouyang, Fang, Mercy, Perou, & Grosse, 2008).

Impulsivity. Impulsivity was operationalized as a latent construct at Waves 2 and 3 using three items. The items were “I rely on my gut feelings,” “I like to live without think- ing about the future,” and “I like to take risks.” All items were assessed on a range from 1 (strongly disagree) to 5 (strongly agree). To evaluate the dimensionality of the items, confir- matory factor analysis was performed and is reported in the Results section (Table 1).

Table 1. Study 1 measurement model estimates of early adversity and impulsivity

Measurement Estimates l SE 95% CI R2

Child abuse & neglect Supervisory neglect 0.57 19.73 [0.36, 0.46]*** .16*** Physical neglect 0.41 17.55 [0.51, 0.63]*** .36*** Physical abuse 0.46 20.99 [0.42, 0.50]*** .19*** Sexual abuse 0.49 12.23 [0.41, 0.57]*** .28***

Impulsivity Wave 2 Like to take risks 0.38 14.92 [0.33, 0.43]*** .13*** Rely on gut feeling 0.59 24.90 [0.55, 0.64]*** .40*** Lack of future thinking 0.51 24.08 [0.47, 0.56]*** .23***

Impulsivity Wave 3 Like to take risks 0.37 17.03 [0.33, 0.41]*** .12*** Rely on gut feeling 0.62 29.32 [0.58, 0.67]*** .46*** Lack of future thinking 0.56 32.03 [0.52, 0.69]*** .27***

Note: Model fit for Study 1 measurement model: x2 (28) ¼ 113.71, p , .01, root mean square error of approx- imation ¼ 0.02, comparative fit index ¼ 0.97, standardized root mean square residual ¼ 0.02. ***p , .01.

Adversity, impulsivity, and drug use 3

Substance use. Substance use was assessed via youth re- port at Waves 3 and 4. Alcohol, cigarette, and cannabis use items evaluated past month’s usage: “How many days in the past 30 days have you used [substance]?” Alcohol and canna- bis usage was scaled from 0 (none) to 6 (every day or almost every day), whereas cigarette usage was the number of days in the last month that the participant smoked at all (0–30).

Covariates. Targets’ age, gender, race/ethnicity (Cauca- sian, African American/Black, Latino, or Asian American) and primary caregivers’ education level (0 ¼ , high school diploma, 1 ¼ high school diploma or GED, 2 ¼ some college and above) were assessed. Because our primary interest is in how child abuse and neglect constitutes a chronically harsh and unpredictable rearing environment, we used posttrau- matic stress disorder (PTSD) as a proxy to control for acute trauma. At Wave 1 and Wave 2, participants were asked if they had ever been diagnosed with PTSD (0 ¼ never diag- nosed, 1 ¼ has been diagnosed). To accommodate the devel- opmental timing in the model, a binary indicator was created based on age at diagnosis of PTSD such that 0 ¼ individuals who were never diagnosed with PTSD or diagnosed after age at Wave 2, and 1 ¼ individuals who were diagnosed with PTSD prior to age at Wave 2.

Data analytic strategy. Hypotheses were tested with struc- tural equation modeling using maximum likelihood estima- tion as implemented in Mplus 7.31 (Muthén & Muthén, 2015). To account for the lack of independence in the data due to cluster sampling within schools, we used the TYPE¼ COMPLEX command (Muthén & Muthén, 2015). A confir- matory factor analysis was first executed to evaluate the mea- surement model for impulsivity and child abuse and neglect. We examined metric and scalar measurement invariance for the impulsivity construct at Waves 2 and 3, assessing model fit changes with criteria of change in comparative factor index (CFI) . 0.01 (Cheung & Rensvold, 2002) and change in Tucker–Lewis index . 0.02 (Vandenberg & Lance, 2000). We then specified an indirect effect model where impulsivity at Wave 3 mediated the influence of child abuse and neglect on each substance use variable at Wave 4; Wave 2 impulsivity and Wave 3 substance use were included as covariates. The standard errors of indirect effects from child abuse and ne- glect to substance use in adulthood were estimated using bootstrapping with 5,000 sample replicates (Preacher & Hayes, 2008). In a final step, we used multiple group analyses to examine if gender moderated the paths linking child abuse and neglect, impulsivity, and substance use.

Results of Study 1

Table 2 presents descriptive statistics and bivariate correla- tions among Study 1 variables. Confirmatory factor analysis supported the measurement model which fit the data as fol- lows: x2 (28) ¼ 113.70, p , .001; CFI ¼ 0.97, root mean square error of approximation (RMSEA) ¼ 0.02, standard

root mean square residual ¼ 0.02. As shown in Table 1, factor loadings were significant, in the correct direction, and ex- ceeded 0.36 for the impulsivity and child abuse and neglect fac- tors. No offending estimates emerged (e.g., negative residual variances or correlations greater than one). In a second anal- ysis, we tested for metric and scalar invariance across time in the impulsivity construct. Results show no significant differ- ences on the CFI and Tucker–Lewis index across time, con- firming measurement invariance from Waves 2 to 3.

We next tested the pathway from child abuse and neglect to each form of substance use at Wave 4 in early adulthood (controlling for Wave 3) via changes in impulsivity from Wave 2 to Wave 3. Participants’ age at Wave 1, PTSD diag- nosis, gender, race, parents’ education level, and family yearly income were included in the model as covariates. Among the control variables, male sex predicted elevated levels of impulsivity (B ¼ –0.03, p , .01), cigarette use (B ¼ –0.15, p , .05), and cannabis use (B ¼ –0.12, p , .01). Age was associated positively with cannabis use (B ¼ –0.02, p , .05). Parental education was positively (B ¼ 0.01, p , .05) associated with cannabis use, and negatively (B ¼ –0.03, p , .05) associated with cigarette use. Parental education (B ¼ –0.004, p , .001) and household income (B ¼ –0.005, p , .001) were negatively associated with im- pulsivity at Wave 3. Diagnosis of PTSD was not significantly associated with impulsivity at Wave 3.

Modification indices suggested estimating cross-lagged paths between Waves 3 and 4 measures of cannabis and ciga- rette use, and eliminating the alcohol use outcome, which was not significantly predicted by impulsivity. In addition, earlier levels of substance use (Wave 2) did not significantly predict impulsivity in Wave 3. Therefore Wave 2 substance use was trimmed from the structural model. The final model and fit in- dices are presented in Figure 1, with parameter estimates shown in Table 3. Child abuse and neglect positively pre- dicted impulsivity at Wave 3 (B ¼ 0.10, p , .001). In turn, im- pulsivity at Wave 3 significantly predicted cigarette use at Wave 4 (B ¼ 0.05, p , .01) and cannabis use at Wave 4 (B ¼ 0.08, p , .001). The indirect effect from child abuse and neglect was significant for cigarette use, B ¼ 0.03, SE ¼ 0.01, 95% confidence interval (CI) [0.003, 0.046], and can- nabis use, B ¼ 0.01, SE¼ 0.01, 95% CI [0.004, 0.023]. A post hoc comparison (Preacher & Hayes, 2008) indicated that the indirect effect from early adversity to cigarette use was signif- icantly larger than the indirect effect from early adversity to cannabis use, B ¼ 0.04, SE ¼ 3.86, 95% CI [0.02, 0.07].

In a final step, using multiple group analyses, we exam- ined if gender modulated the paths linking child abuse and neglect to impulsivity and impulsivity to each substance use type. No significant gender differences in model paths emerged.

Discussion of Study 1

Using longitudinal data spanning middle adolescence (mean age ¼ 15 years) to young adulthood (mean age ¼ 28 years),

A. Oshri et al.4

Table 2. Study 1 descriptive statistics and bivariate correlations of study variables

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Controls 1. Age W1 — 2. Sex 2.05** — 3. Race 2.06** 2.01 — 4. Parental education W1 2.08** 2.02* .08** — 5. Family yearly income W1 .00 .00 .13** .27** — 6. PTSD W1 .02* .00 .01 2.01 2.01 —

Child abuse and neglect 7. Supervisory neglect 2.03** 2.04** 2.03** .02 2.05** .02 — 8. Physical neglect .00 2.05** 2.08** 2.06** 2.06** .01 .22** — 9. Physical abuse .02* 2.03** 2.03** 2.02 2.04** .03** .30** .17** —

10. Sexual abuse .01 .05** 2.03** 2.02* 2.03* .08** .11** .19** .20** — Impulsivity 11. Gut feeling W2 2.03** 2.07** 2.05** 2.10** 2.07** 2.01 .01 .06** 2.01 .04** — 12. Gut feeling W3 .01 2.08** 2.07** 2.12** 2.08** .00 .04** .09** 2.01 .06** .25** — 13. Risk taking W2 2.02* 2.15** .08** .01 .00 .00 .05** .01 .04** .01 .22** .14** — 14. Risk taking W3 2.03** 2.22** .00 .01 .01 2.02* .05** .03** .01 .02 .10** .24** .33** — 15. Lacking future thought W2 2.02** 2.12** 2.01 2.14** 2.06** .00 .03** .06** .00 .22* .31** .19** .19** .08** — 16. Lacking future thought W3 .02* 2.14** 2.04** 2.14** 2.07** .02* .04** .09** 2.01 .05** .19** .34** .11** .21** .27** — Substance use 17. Cigarette use W3 2.01 2.06** .20** 2.02* 2.04** .05** .06** .04** .06** .02* .09** .09** .13** .07** .07** .08** — 18. Cigarette use W4 2.02* 2.08** .12** 2.05** 2.06** .02* .04** .08** .05** .03** .11** .12** .11** .07** .11** .10** .63** — 19. Cannabis use W3 2.01 2.09** .00 .03** .00 .00 .05** .05** .04** .01 .04** .06** .06** .07** .05** .07** .12** .12** — 20. Cannabis use W4 2.03** 2.12** .01 .02* 2.01 .00 .06** .02 .06** .01 .07** .10** .08** .10** .05** .09** .21** .26** .27** —

Mean 15.22 1.51 0.63 5.46 46.66 0.00 1.10 0.31 0.81 0.11 2.98 2.80 3.53 3.45 2.44 2.20 7.78 7.96 3.73 0.63 SD 1.65 0.50 0.48 2.39 51.20 0.05 1.61 1.01 1.48 0.57 1.15 1.18 1.05 1.06 1.08 1.04 12.60 12.55 20.54 1.62

Note: W1–W4, Waves 1–4 of data collection; PTSD, posttraumatic stress disorder. Sex was coded as male ¼ 1 and female ¼ 2; race was coded as Caucasian ¼ 1 and others ¼ 0; N ¼ 9,421. *p , .05. **p , .01.

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we tested the hypothesis that impulsivity would, in part, ex- plain the effects of child abuse and neglect on the frequency of substance use in young adulthood. Informed by develop- mental models regarding neurocognitive adaptations to stressful and unpredictable environments (Cicchetti & Ro- gosch, 2002; Del Giudice et al., 2011), the findings from our study were largely consistent with our hypotheses. Expo- sure to child abuse and neglect was associated with increased impulsive behaviors from middle to late adolescence, which, in turn, predicted cigarette and cannabis use in young adult- hood. The data further indicated that child abuse and neglect was indirectly associated with cigarette and cannabis use via impulsivity. These findings are consistent with the proposi- tion that exposure to child abuse and neglect is linked to a cognitive preference for short- versus long-term rewards (Thibodeau et al., 2015). For young people who experience child abuse and neglect, the environment is thought to be par- ticularly harsh, unpredictable, and stressful. Such rearing contexts are hypothesized to provide little reinforcement for delaying gratification in the hope of larger rewards in the fu- ture. Over time, the developing child “learns” to prefer im- mediate rewards, resulting in a tendency toward impulsive de- cision making. These cognitive adaptations, in turn, are well established proximal antecedents to substance use (Bickel & Marsch, 2001; Koob & Kreek, 2007).

Our findings, however, failed to find an impulsive behav- ior pathway for young adults’ use of alcohol. Although past studies have linked impulsivity to alcohol use, results are in- consistent (cf. Wiers, Ames, Hofmann, Krank, & Stacy, 2010). This inconsistency in our study and others may be

due to the presence of high levels of normative use of alcohol during young adulthood. Because alcohol consumption is highly prevalent, other predictors such as social norms for use may overshadow the potential influence of impulsive de- cision making. Impulsivity in this age group may be associ- ated primarily with clinically relevant substance use rather than normative levels of use in this age group. Additional re- search is needed that makes distinctions between normative and problematic drinking patterns. An additional hypothesis regarding inconsistency in links between impulsivity and al- cohol use involves the multidimensionality of impulsivity. Studies suggest that impulsivity is a multidimensional con- struct with subcomponents having differential predictive util- ity on different substances (Adams, Kaiser, Lynam, Char- nigo, & Milich, 2012; Verdejo-Garcı́a, Bechara, Recknor, & Pérez-Garcı́a, 2007; Zapolski, Cyders, & Smith, 2009). Thus specific aspects of impulsivity that were not measured in the present study may have links to alcohol use.

This study has both important strengths and limitations. The use of a nationally representative sample of youth and young adults is useful for examining broad hypotheses in a population with repeated measures of impulsivity and sub- stance use. Large representative data sets such as Add Health, however, often lack fine-grained measures of key constructs as well as multimethod assessments. For example, our assess- ment of impulsivity relied on three items selected by Add Health investigators rather than established multiple-item in- ventories. Additional research that provides a more diverse and high-resolution assessment of impulsivity is needed. This is addressed in Study 2 below.

Figure 1. Longitudinal findings for childhood abuse and neglect and substance use (Add Health). Standardized parameter estimates are shown. W, wave of data; adolescent age, alcohol use at Wave 1, gender, posttraumatic stress disorder diagnosis, and parental education are covariates (not shown for clarity). *p , .05, **p , .01, ***p , .001. N ¼ 9,139.

A. Oshri et al.6

Caution must be exercised in interpreting the data due to limitations inherent in retrospective self-reports of childhood abuse and neglect. Past studies support the reliability of self- reports of adverse childhood experiences particularly when relatively little time has passed in recalling major traumatic events such as child abuse and neglect (Hardt & Rutter, 2004). However, retrospective measures remain vulnerable to recall biases. Studies suggest that the correspondence be- tween prospective and retrospective reports of child maltreat- ment is moderate (F ¼ 0.27; Tajima, Herrenkohl, Huang, & Whitney, 2004), and that underreporting is common. This suggests that the strength of the association between child maltreatment and impulsivity may be underestimated in the present study. Future research that uses different methods and reporters is needed to avoid Type I error emanating from shared method variance. Despite these limitations, the present study provides evidence of impulsivity acting as a mechanism linking child abuse and neglect to substance use in young adulthood.

Study 2

Evidence from Study 1 and other research reviewed above (Thibodeau et al., 2015) suggests that impulsivity may partially account for observed links between adverse childhood experi- ences and substance use. In Study 2 our goal is to provide a more comprehensive and nuanced examination of impulsivity

as a mechanism linking adversity and substance use. First, we operationalized impulsivity using two distinct assessment para- digms: a trait-related perspective and a neuroeconomic one. Then we investigated specific subcomponents of impulsivity that may bear differential associations with exposure to child- hood adversity and with substance use type and frequency.

Delayed reward discounting, child abuse and neglect, and substance use

The operationalization of impulsivity in Study 1 was informed by trait-related perspectives on impulsivity (Patton & Stanford, 1995). Recently, the utility of a neuroeconomic paradigm for assessing impulsivity has been documented in the study of substance use (MacKillop et al., 2011). Neuroeconomics, a multidisciplinary perspective integrating decision making, neurocognitive science, and behavioral economics, has investi- gated impulsivity from the paradigm of delayed reward discounting. Analogous to the ability to delay gratification, de- layed reward discounting captures an individual’s preference for smaller and immediate, rather than larger and delayed, re- wards. A tendency to prefer immediate over delayed rewards is thought to manifest in a preference for valuing the short- term benefits of substance use rather than the consideration of negative sequelae that may ensue from substance use (Am- lung, Vedelago, Acker, Balodis, & MacKillop, 2016; Bickel, Yi, Landes, Hill, & Baxter, 2011; De Wit, 2009).

Table 3. Study 1 parameter estimates of the paths effects models of child abuse and neglect, impulsivity, and substance use

B SE b 95% CI

Direct Effects

Child abuse & neglect Impulsivity W3 0.03 0.10 0.10 [0.012, 0.041]*** Cigarette use W4 0.00 0.11 0.00 [20.226, 0.218] Cannabis use W4 0.08 0.04 0.05 [0.013, 0.156]*

Impulsivity W3 Cigarette use W4 0.94 0.32 0.05 [0.299, 1.570]** Cannabis use W4 0.50 0.13 0.08 [0.249, 0.755]***

Cross-Lagged Effects

Impulsivity W2 impulsivity W3 0.47 0.05 0.49 [0.367, 0.568]*** Cannabis use W3 cannabis use W4 0.01 0.00 0.29 [0.008, 0.018]*** Cannabis use W3 cigarette use W4 0.00 0.00 0.02 [20.002, 0.007] Cigarette use W3 cigarette use W4 0.15 0.01 0.95 [0.143, 0.166]*** Cigarette use W3 cannabis use W4 0.01 0.00 0.17 [0.008, 0.012]***

Indirect Effects

Child abuse & neglect impulsivity W3 cigarette use W4 0.03 0.01 0.004 [0.003, 0.046]* Child abuse & neglect impulsivity W3 cannabis use W4 0.01 0.01 0.007 [0.004, 0.023]*

Note: Model fit for Study 1: x2 (139) ¼ 940.90, p , .01, root mean square error of approximation ¼ 0.03, comparative fit index ¼ 0.89, standardized root mean square residual ¼ 0.03. Study 1 used age, sex, ethnicity, parent’s education level, family yearly income, and posttraumatic stress disorder as cov- ariates in these analyses. W2–W4, Waves 2–4 of data. *p , 0.5. **p , 0.01.

Adversity, impulsivity, and drug use 7

Delayed reward discounting is assessed with a task-based measure where an individual chooses his or her preference for monetary rewards that vary in size and delay in time of re- ceipt. This task indexes how quickly rewards lose value as a function of their receipt latency (MacKillop et al., 2011). Nu- merous cross-sectional studies have found that individuals with substance use disorders demonstrate significantly greater preferences for short-term rewards compared to control partic- ipants (Bickel & Marsch, 2001; MacKillop et al., 2007; Madden, Bickel, & Jacobs, 1999; Petry, 2001). Longitudinal studies indicate that impulsive discounting predicts the onset of addictive behavior (Audrain-McGovern et al., 2009; Fernie et al., 2013). Evidence from a meta-analysis of case-control studies suggests that the link between delayed reward discount- ing and substance use is robust across studies and of medium magnitude (Cohen d ¼ 0.58; MacKillop et al., 2011).

Recent evidence suggests that task-based discounting measures and self-reported impulsivity scales may assess dis- tinct aspects of impulsive decision making. In general, these measures are only modestly associated (Cyders & Coskunpi- nar, 2011) and may have differential predictive validity when examining substance use. For example, Mitchell, Fields, D’esposito, and Boettiger (2005) found that compared to self-report measures of impulsivity, a delayed discounting task better differentiated between normative and problematic use of alcohol. In contrast, other research (Jones, Fearnley, Panagiotopoulos, & Kemp, 2015) found the opposite, with self-reported impulsivity measures better predicting sub- stance use in a sample of high-risk Australian youth. Given disparate findings, researchers have called for additional stud- ies that examine the predictive effects of impulsivity obtained by self-reports compared to behavioral tasks such as delayed discounting (Cyders & Coskunpinar, 2011). Thus, the first aim of this study is to examine a model of impulsivity as a me- diator of the link between adversity and substance use incor- porating both trait-related and discounting perspectives on and measures of impulsivity.

A multidimensional model of impulsivity and substance use

Recent research has documented reliable subcomponents of impulsivity that may have differential predictive validity in modeling the etiology of substance use. Whiteside and Lynam (2001) advanced and validated a multidimensional model of impulsive behaviors. These include urgency (i.e., proneness to act out during negative mood states), lack of pre- meditation (i.e., tendency to plan ahead), lack of persever- ance (i.e., inability to persists in an activity), and sensation seeking (i.e., orientation to novel and stimulating experi- ences), which are a theory and a related instrument known as the urgency, premeditation, perseverance, and sensation seeking subscales (UPPS). Subsequently, replacing the single urgency component, a fifth factor of impulsivity was added, deriving distinct positive and negative urgency dimensions (Cyders & Smith, 2007). Considerable research supported

the factorial validity of the five impulsivity factors and their predictive validity regarding substance use and abuse (Am- lung et al., 2016; Verdejo-Garcı́a et al., 2008; Whiteside & Lynam, 2001).

All subcomponents of impulsivity defined by the UPPS and positive urgency subscales (UPPS-P) have been linked to substance use behaviors, with more consistent associations occurring for alcohol use (Simons, Dvorak, Batien, & Wray, 2010; Whiteside, Lynam, Miller, & Reynolds, 2005). Lack of premeditation and positive and negative urgency, however, demonstrate robust and consistent associations with a range of different substances (Adams et al., 2012; Verdejo-Garcı́a et al., 2007; Zapolski et al., 2009). Moreover, examinations of urgency as an antecedent of substance use have provided insights into differential motivational pathways to substance use behaviors. For example, negative urgency has been found to influence problematic drinking primarily through coping motives (Adams et al., 2012). The experience of negative ur- gency, a tendency to act impulsively when experiencing negative emotions, encourages substance use as a coping strategy to soothe emotional distress (Carpenter & Hasin, 1999). In contrast, for individuals who exhibit positive ur- gency, substances are used to reinforce and extend a positive mood (Cyders & Smith, 2007, 2008). Thus, identifying how specific aspects of impulsivity affect substance use provides valuable insights into the etiology and course of young adult substance abuse.

Adverse childhood experiences and impulsivity

Research investigating the contextual antecedents of impul- sivity in general, and UPPS dimensions, in particular, is not- ably absent. In Study 2, we investigated the influence of ad- verse childhood experiences on distinct aspects of impulsive behavior. Neurocognitive studies implicate multiple systems associated with the regulation of impulse control, reward, and emotion regulation in the development of impulsive de- cision making (Koob & Kreek, 2007). Harsh rearing environ- ments have neurobiological effects on all of these systems (Heim & Nemeroff, 2002; Pechtel & Pizzagalli, 2011; Sinha & Jastreboff, 2013). Given the multiple systems involved, it is plausible that adversity may affect several subcomponents of impulsivity or potentially exhibit specific effects on particular dimensions. The existence of various motivations for engag- ing in substance use that are related to distinct aspects of im- pulsivity necessitates investigations of contextual factors that affect distinct impulsivity dimensions and can yield valuable information regarding the etiology of substance use. We thus explore the associations between adverse childhood experi- ences and impulsivity subcomponents in the present study.

Gender differences in the adversity, impulsivity, and substance use pathway

As noted in Study 1, the potential for gender differences in the pathways linking childhood adversity, impulsivity, and

A. Oshri et al.8

substance use requires investigation. Although men tend to score higher on measures of trait impulsivity (Cross et al., 2011), studies using delay discounting or executive function tasks, however, find inconsistent results, often depending on the kinds of rewards that characterize the task (Chapple & Johnson, 2007). Few studies have examined the gender dif- ferences in the associations among childhood adversity, im- pulsivity, and substance use, particularly when both measures of trait impulsivity and delay reward discounting are admin- istered. Thus, in the present study gender differences were investigated in the associations between adverse childhood experiences and impulsivity and between impulsivity and substance use.

Methods

Sample. Participants were recruited and data were collected using Amazon’s Mechanical Turk (M-Turk) Web-based data collection platform. M-Turk is an online system that links users who are interested in participating in research stud- ies (that can be administered online) with researchers seeking participants who meet their eligibility criteria. The platform also integrates a convenient consent and data collection pro- cess for participants. Participants receive modest incentives for their participation as set by the study investigator. Studies that have examined the representativeness and quality of data that M-Turk yields have been promising. M-Turk yields ra- cially and ethnically diverse samples that are representative of young adults who do not attend college (Berinsky, Huber, & Lenz, 2012). Studies of M-Turk data quality find reliability and concurrent validity coefficients that are similar and in some cases exceed those using face-to-face data collection platforms (Mason & Suri, 2012). Data quality and sample representatives do not appear to be significantly affected by variability in in- centive rates offered on M-Turk (Buhrmester, Kwang, & Gosling, 2011; Goodman, Cryder, & Cheema, 2013).

In this study, participants were recruited using the follow- ing inclusion criteria: (a) 18þ years old and (b) geographi- cally located in the United States. Participants signed an elec- tronic consent form approved by the university institutional review board and received $1 for their participation. The sam- ple comprised 1,011 individuals (41% male, 59% female), with a mean age of 32 years (SD ¼ 11.44), median annual in- come of $30,000–$44,999, and mean years of education of 15.29 (SD ¼ 2.76). The sample was predominantly Cauca- sian (76.8%), with smaller proportions self-reporting African American (10.1%), multiracial (5.3%), Asian (4.1%), and Native American/Alaskan Native (1.2%) race.

Measures.

Child abuse and neglect. Child abuse and neglect was op- erationalized as a latent variable at Time 1 using items from the Adverse Childhood Experiences instrument (Hardt & Rutter, 2004). Four items on child abuse and neglect address the occurrence of neglect, emotional abuse, physical abuse,

and sexual abuse prior to age 16. Studies support the reliabil- ity and validity of the Adverse Childhood Experiences instru- ment when used with young adults from diverse racial/ethnic and gender groups (Koss et al., 2003; Ramiro, Madrid, & Brown, 2010). To evaluate the unidimensionality of the four items, confirmatory factor analysis was performed and reported in the Results section.

Substance use. Participants’ alcohol use in the past 3 months was assessed with a three-item subscale of the Alco- hol Use Disorders Identification Test (a ¼ 0.87; Saunders, Aasland, Babor, De la Fuente, & Grant, 1993). Participant cigarette and marijuana use were characterized by self- reported use over the last 3 months using single items. Re- sponse options ranged from 0 (none) to 4 (multiple times daily).

Delayed reward discounting. Delayed reward discounting was assessed with the Monetary-Choice Questionnaire (Am- lung & MacKillop, 2014; Kirby, Petry, & Bickel, 1999). It comprises 54 dichotomous choices that range in size of the reward and delay to receipt. Example items include “Would you rather have $19 today or $25 in 53 days” and “Would you rather have $49 today or $60 in 89 days.” A k value is cal- culated from the individual’s point of indifference (i.e., the amount of immediate money that is equal to a larger delayed amount of money for that individual) across multiple delays. The k value, or “discounting rate,” represents the rate at which an individual devalues a reward based on its delay. A higher k value indicates a steeper discounting rate and suggests a stronger preference for smaller, immediate rewards. As is common, the k values were skewed and were thus all logarith- mically transformed.

Impulsivity. Participants completed the Impulsive Behav- ior Scale (Whiteside & Lynam, 2001), a 59-item measure that assesses five dimensions of impulsivity, including posi- tive/negative urgency (e.g., “When I feel bad/good, I will of- ten do things I later regret in order to make myself feel better now”; a ¼ 0.91 for negative urgency; a ¼ 0.96 for positive urgency), lack of premeditation (e.g., “I am one of those peo- ple who blurt out things without thinking”; a¼ 0.87), lack of perseverance (e.g., “I tend to give up easily”; a ¼ 0.86), and sensation seeking (e.g., “I quite enjoy taking risks”; a ¼ 0.87). Each item on the UPPS-P is rated on a 4-point Likert scale from 1 (strongly agree) to 4 (strongly disagree). Studies have confirmed the factor structure of the UPPS-P (Cyders, 2013; Lynam, Miller, Miller, Bornovalova, & Lejuez, 2011) and support its predictive validity in substance use re- search (Magid & Colder, 2007; Zapolski et al., 2009).

Covariates. Participant age, gender, parent education, and financial stress were included as covariates. Financial stress was assessed using a single item that asked about the partic- ipant’s current financial situation. Response options ranged

Adversity, impulsivity, and drug use 9

from 1 (not enough to pay bills) to 4 (enough for extras). Par- ent’s education was assessed as years of schooling received.

Data analytic strategy. Study hypotheses were tested with structural equation modeling using Mplus version 7.31 (Mu- thén & Muthén, 2015). We first examined measurement mod- els specifying latent child abuse and neglect and impulsive personality constructs. The child abuse and neglect confirma- tory factor analysis was modeled with four binary items using a robust weighted least squares estimator (Muthén, du Toit, & Spisic, 1997). This model estimates probit regressions for the factor indicators regressed on the factor, resulting in an under- lying continuous latent variable of child abuse and neglect. The UPPS-P latent construct and the delayed reward dis- counting k value index were then specified as indirect effects linking childhood adversity to alcohol, cigarette, and canna- bis use. For these analyses, significance testing applied the Holm-based Bonferroni correction (Jaccard & Guilamo-Ra- mos, 2002). Subsequently, we examined the indirect effect of each UPPS-P subscale using parallel mediation analyses (Preacher & Hayes, 2008). The significance of indirect paths was tested with the product coefficient method (delta) using the maximum likelihood estimator.

Results of Study 2

Preliminary analyses. Table 4 presents descriptive statistics and the bivariate correlations for the study variables. The measurement model is presented in Table 5. The model fit the data well: x2 (21) ¼ 36.06, p ¼ .02; CFI ¼ 0.99, RMSEA ¼ 0.03, weighted root mean square residual (WRMR) ¼ 0.75. As shown in Table 5, factor loadings were significant, in the correct direction, and exceeded 0.36, with the exception of sensation seeking (0.24). No offending estimates were pres- ent in the analyses (i.e., negative residual variances, correla- tions greater than 1, or modification indices greater than 4.0).

Indirect effects via latent impulsivity and delayed reward dis- counting. We examined the pathway from child abuse and ne- glect to substance use through the impulsivity factor and the delay discounting variable. The model was tested initially with age, gender, and financial stress controlled. The model fit the data as follows: x2 (74) ¼ 169.58, p , .01; CFI ¼ 0.97, RMSEA ¼ 0.03, WRMR ¼ 1.05. Youth age was asso- ciated negatively with cannabis use (B ¼ –0.01, p , .01). Fi- nancial stress was associated negatively with delayed reward discounting (B ¼ –0.01, p , .01).

Child abuse and neglect was significantly associated with the impulsivity construct (B ¼ 0.20, p , .01) and the delay discounting measure (B ¼ 0.01, p , .05; Figure 2). The im- pulsivity construct was significantly and positively associated with alcohol (B ¼ 0.56, p , .01), cigarette (B ¼ 0.29, p , .01), and cannabis use (B ¼ 0.12, p , .01), whereas delay discounting was significantly associated only with cannabis (B ¼ 0.81, p , .05) and cigarette use (B ¼ 2.58, p , .01).

The indirect effect from child abuse and neglect to sub- stance outcomes via the UPPS-P was significant for alco- hol use (B ¼ 0.11, SE ¼ 4.63, 95% CI [0.06, 0.16]), cigarette use, B ¼ 0.06, SE ¼ 3.44, 95% CI [0.02, 0.09], and cannabis use, B ¼ 0.03, SE ¼ 3.17, 95% CI [0.01, 0.04]. The indirect effect from child abuse and neglect to cigarette use via delay discounting was significant as well, B ¼ 0.02, SE ¼ 2.02, 95% CI [0.001, 0.03], though the indirect effect for cannabis use was not, B ¼ 0.01, SE ¼ 1.47, 95%CI [20.002, 0.01]. To examine the relative strengths of these indirect effects, post hoc comparisons were conducted (Preacher & Hayes, 2008). These comparisons indicated that for cigarette use, the impulsivity construct was a significantly stronger media- tor of child abuse and neglect than was delayed reward dis- counting (DB ¼ 0.04, p , .05). The impulsivity factor most strongly mediated the effect of child abuse and neglect on alcohol use (DB ¼ 0.06, p , .01), followed by cigarette use (DB ¼ 0.03, p , .05). Finally, the strength of the impul- sivity construct as a mediator between child abuse and ne- glect and substance use was the weakest for cannabis use (DB ¼ 0.01, p , .01) when compared to either alcohol or cig- arette use.

Gender differences in the paths between adverse early childhood experiences and impulsivity/delayed reward dis- counting and impulsivity/delayed reward discounting to alco- hol, cigarette, and cannabis use were examined with multiple group analyses. No significant differences in the path coeffi- cients emerged based on sex.

Indirect effects via subcomponents of impulsivity. To clarify the associations among child abuse and neglect, specific sub- components of impulsivity, and substance use outcomes, a par- allel indirect effects model was used (Preacher & Hayes, 2008). Specifically, the five subscales of the UPPS-P were modeled concurrently to test their independent role as indirect effects be- tween adverse childhood experiences and alcohol, nicotine, and cannabis use. Financial stress, gender, and age were included as covariates. Model fit was acceptable: x2 (4) ¼ 38.82, p , .01; CFI ¼ 0.98, RMSEA ¼ 0.09, standard root mean square resid- ual ¼ 0.02. Financial stress was significantly associated with negative urgency (B ¼ –0.10, p , .01) and sensation seeking (B ¼ 0.04, p , .01). Males evinced higher levels of sensation seeking (B ¼ –0.30, p , .01) and positive urgency (B ¼ –0.20, p , .01) than did females. Younger individuals reported higher levels of sensation seeking (B ¼ –0.01, p , .01) and negative urgency (B ¼ –0.01, p , .01) than did older individuals. As shown in Table 6, adverse childhood experiences were associ- ated significantly with negative urgency (B ¼ 0.05, p , .01), positive urgency (B ¼ 0.02, p , .01), and sensation seeking (B ¼ 0.03, p , .01); no significant effects emerged for lack of premeditation (B ¼ 0.01, p ¼ ns) or lack of perseverance (B ¼ 0.01, p ¼ ns). Alcohol use was significantly associated with negative urgency (B ¼ 0.25, p , .01), sensation seeking (B ¼ 0.15, p , .05), and lack of premeditation (B ¼ 0.21, p , .05). Cannabis use was significantly associated with negative urgency (B ¼ 0.09, p , .05), sensation seeking (B ¼ 0.07, p ,

A. Oshri et al.10

Table 4. Study 2 cross-sectional study descriptive statistics and bivariate correlations of study variables

Variables 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

Controls 1. Age — 2. Gender 2.03 — 3. Parent education .10** 2.01 — 4. Financial stress 2.07* 2.02 .09** —

Child abuse & neglect 5. Verbal abuse .00 2.04 2.11** 2.12** — 6. Physical abuse .01 2.03 2.09** 2.10** .68** — 7. Sexual abuse .00 2.2 2.03 2.02 .31** .32** — 8. Emotional neglect .03 2.03 2.11** 2.13** .55** .47** .35** —

Impulsivity constructs 9. Delay discounting 2.02 .03 2.13** 2.21** .09** .10** .06 .05 —

10. Negative urgencya 2.11** 2.03 2.11** 2.15** .19** .17** .16** .21** .11** — 11. Premeditationa .03 2.02 .03 2.05 .01 .05 .01 .01 .04 .43** — 12. Perseverancea 2.07* .01 2.06 2.14** .09** .07* .03 .09** 2.01 .48** .51** — 13. Positive urgencya 2.09** .01 2.08* 2.05 .07* .11** .06 .05 .09** .73** .44** .39** — 14. Sensation seekingb 2.18** .03 2.00 .09** .01 .08** .04 .01 .01 .17** .11** 2.12** .29** — Substance use 15. Alcoholc 2.10** .03 2.07* .02 .04 .06* .05 .02 .06 .25** .21** .14** .26** .17** — 16. Cigarettec .03 .02 2.15** 2.10** .12** .14** .05 .12** .18** .25** .15** .06 .19** .12** .31** — 17. Cannabisc 2.25** .01 2.16** 2.06 2.04 .04 .00 .00 .11* .21** .02 .11* .19** .15** .19** .26** —

Mean 32.67 0.58 15.29 2.36 1.35 1.26 1.14 1.28 0.00 2.21 1.97 2.00 2.51 1.83 1.67 0.49 1.25 SD 11.44 0.49 2.76 1.01 0.48 0.44 0.35 0.45 1.00 0.62 0.47 0.49 0.60 0.63 1.11 0.81 0.39

aUrgency, urgency, premeditation, perseverance, sensation seeking, and positive urgency impulsive behavior scale subscale composites. Gender was coded as male ¼ 0 and female ¼ 1. bTransformed with a square root. cAUDIT, Alcohol Use Disorder Identification Test composite score last 3 months. *p , .05. **p , .01.

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.05), and lack of premeditation (B ¼ –0.10, p , .05). Finally, cigarette use was significantly associated with negative urgency (B ¼ 0.30, p , .01), lack of premeditation (B ¼ 0.22, p , .01), and lack of perseverance (B ¼ –0.18, p , .01).

Next, we tested the significance of indirect effects after trimming nonsignificant mediators from the model (i.e., lack of premeditation or lack of perseverance). The resulting model fit the data as follows: x2 (13) ¼ 87.63, p , .01; CFI ¼ 0.96, RMSEA ¼ 0.06, WRMR ¼ 1.33; direct and indirect ef- fects are presented in Table 3 and Figure 3. Indirect effect analyses revealed that all three impulsivity subscales signifi- cantly mediated the link from adverse childhood experiences

to alcohol use, whereas negative urgency, B ¼ 0.005, SE ¼ 1.93, 95% CI [0.001, 0.01], and sensation seeking, B ¼ 0.002, SE ¼ 2.30, 95% CI [0.001, 0.005], mediated the link from adverse childhood experiences to cannabis use. Only negative urgency mediated the link from adverse child- hood experiences to cigarette use, B ¼ 0.02, SE ¼ 3.49, 95% CI [0.01, 0.02].

Discussion of Study 2

We investigated the indirect influences of delay discounting and self-reported impulsivity on the link between adverse

Table 5. Study 2 measurement model estimates of early adversity and impulsivity (UPPS-P)

Measurement Estimates l SE 95% CI R2

Child abuse & neglect Sexual abuse 0.67 15.63 [0.58, 0.78]*** .45*** Physical abuse 0.81 19.97 [0.73, 0.89]*** .66*** Verbal abuse 0.86 21.35 [0.78, 0.94]*** .75*** Emotional neglect 0.88 23.43 [0.81, 0.96]*** .78***

Impulsivity (UPPS-P) Positive urgency 0.75 36.94 [0.72, 0.80]*** .57*** Negative urgency 0.99 40.35 [0.94, 1.04]*** .98*** Lack of premeditation 0.42 14.94 [0.36, 0.47]*** .18*** Lack of perseverance 0.49 20.27 [0.45, 0.54]*** .25*** Sensation seeking 0.24 8.37 [0.19, 0.30]*** .06***

Note: Model fit for Study 1 measurement model: x2 (21) ¼ 36.06, p , .05, root mean square error of approx- imation ¼ 0.03, comparative fit index ¼ 0.99, weighted root mean square residual ¼ 0.93. UPPS-P, urgency, premeditation, perseverance, sensation seeking, and positive urgency subscales.

Figure 2. Study 2 child abuse and neglect, UPPS-P, discounting, and standard use. Standardized parameter estimates shown. Age, gender, and financial stress are covariates. *p , .05, **p , .01.

A. Oshri et al.12

childhood experiences and past 3 months’ substance use. Findings supported the importance of investigating associa- tions between substance use and different aspects and con- ceptualizations of impulsivity, obtained by self-report and task-based measures. We found evidence to support the po- tential for delayed reward discounting and a latent impulsivity construct to transmit the influence of adverse childhood ex- periences to substance use. These putative mediators were in- dependent of each other, suggesting distinct impulsivity- related pathways that are affected by childhood adversity. The discounting path was most robust in explaining cigarette use, although mediation was evident for the use of other sub- stances as well. In a set of dismantling analyses, we examined the unique contributions of different UPPS-P subscales in connecting adverse childhood experiences to substance use. Child abuse and neglect was significantly associated with negative urgency, positive urgency, and sensation seeking, but not significantly associated with lack of premeditation or lack of perseverance. Negative urgency, positive urgency, and sensation seeking indirectly connected child abuse and neglect to alcohol use, whereas negative urgency and sensa- tion seeking indirectly linked child abuse to cannabis use. Finally, child abuse and neglect and cigarette use were

indirectly associated via negative urgency. These results sup- port research that has suggested that impulsivity is a heteroge- neous construct with differential association across risk be- haviors (Cyders & Smith, 2008; Smith et al., 2007; Whiteside & Lynam, 2001).

Past research has noted that discounting and self-reported measures of impulsivity are only modestly associated and there are inconsistent associations between different concep- tualizations of impulsivity and substance use (Cyders & Cos- kunpinar, 2011). In our study, the constructs were distinct (no association) although both demonstrated independent asso- ciations with child abuse and neglect. These links supported the theoretical contention that child abuse and neglect is linked to a neurocognitive adaptation resulting in impulsive behavior, providing complementary and distinct forms of im- pulsivity measurement. In addition, the findings document the pathways from adverse rearing environment and sub- stance use with greater specificity of the associations between the factor of child abuse and neglect and the modeled impul- sivity dimensions. In examining the influence of impulsivity on substance use, delay discounting only predicted cigarette use, whereas self-reported impulsivity predicted all three form of substance use. Across studies, discounting has been

Table 6. Study 2 direct and indirect paths predicting dimensions of impulsivity, and substance use

Direct Effects Impulsivity Dimensions B SE b 95% CI

Child abuse & neglect Negative urgency 0.238 0.038 0.259 [0.163, 0.313]*** Positive urgency 0.121 0.036 0.130 [0.049, 0.192]** Sensation seeking 0.107 0.035 0.119 [0.038, 0.175]** Alcohol use 0.054 0.071 0.033 [20.085, 0.193] Cigarette use 0.097 0.056 20.082 [20.013, 0.207] Cannabis use 20.046 0.033 0.077 [20.111, 0.018]

Negative urgency Alcohol use 0.125 0.100 0.071 [20.070, 0.321] Cannabis use 0.193 0.063 0.315 [0.069, 0.317]** Cigarette use 0.241 0.107 0.176 [0.032, 0.451]*

Positive urgency Alcohol use 0.355 0.098 0.204 [0.163, 0.546]*** Cannabis use 20.071 0.061 0.117 [20.190, 0.048] Cigarette use 0.039 0.097 0.029 [20.151, 0.229]

Sensation seeking Alcohol use 0.219 0.063 0.121 [0.096, 0.343]*** Cannabis use 0.098 0.032 0.156 [0.035, 0.162]** Cigarette use 0.098 0.049 0.070 [0.002, 0.195]*

Indirect Effects of Adversity on Substance Use B SE a*b 95% CI

Child abuse & neglect NU alcohol use 0.030 0.408 0.018 [20.017, 0.077] Child abuse & neglect NU cannabis use 0.046 0.556 0.082 [0.012, 0.080]** Child abuse & neglect NU cigarette use 0.057 0.244 0.058 [0.004, 0.110]* Child abuse & neglect PU alcohol use 0.043 0.199 0.026 [0.009, 0.077]* Child abuse & neglect PU cannabis use 20.009 0.271 20.015 [20.024, 0.007] Child abuse & neglect PU cigarette use 0.005 0.119 0.046 [20.018, 0.028] Child abuse & neglect SEN alcohol use 0.023 0.038 0.014 [0.005, 0.042]* Child abuse & neglect SEN cannabis use 0.011 0.050 0.019 [0.001, 0.020]* Child abuse & neglect SEN cigarette use 0.010 0.022 0.004 [20.002, 0.023]

Note: NU, negative urgency; PU, positive urgency; SEN, sensation seeking. Model fit is as follows: x2 (45) ¼ 191.68, p , 0.01; comparative fit index ¼ 0.96, root mean square error of approximation ¼ 0.06, weighted root mean square residual ¼ 1.33. Age, gender, and financial stress are used as covariates (not shown for brevity). *p , .05. **p , .01, ***p , .001.

Adversity, impulsivity, and drug use 13

particularly robust in predicting behavior in clinical samples (MacKillop et al., 2011). It may be the case in our findings that cigarette users were more likely to be experiencing de- pendence and thus the discounting measure is especially sen- sitive to cigarette use. In contrast, discounting appears to be less robust as a predictor of nonclinical levels of substance use such as that reported for alcohol and marijuana by the vast majority of our sample. From a developmental psychopa- thology perspective, it is possible that self-reported impulsiv- ity captures an early stage of vulnerability in the pathway to problematic substance use whereas delay discounting reflects a more advanced stage in addiction. Further research is needed to examine temporal associations between forms of impulsivity as well as to better understand the neurocognitive processes being assessed.

In our analyses of the unique effects of distinct UPPS-P subscales, we found associations between child abuse and ne- glect and (a) positive and negative urgency and (b) sensation seeking. The links between these subscales and substance use were complex, with only negative urgency predicting all three substances. The pattern of findings suggests that negative ur- gency is a robust indirect effect linking adversity to substance use. This is consistent with a recent study that found that child maltreatment independently predicted negative urgency net of other aspects of impulsivity (Gagnon, Daelman, McDuff, & Kocka, 2013). From a developmental perspective, child ad- versity affects multiple systems that regulate threat sensitivity and emotion processing (Kim & Cicchetti, 2010; Maughan & Cicchetti, 2002; Morris et al., 2007). Adverse childhood ex- periences may present significant threats to the optimal devel-

opment of emotional understanding and regulation, partly due to chaotic or hostile interactions in the household. In such environments, children are less likely to learn effective strate- gies to regulate their emotional states. An unpredictable and disorganized environment would make children particularly vulnerable to frequent negative emotional experiences, includ- ing anger, frustration, reactivity, and irritability (Alessandri, 1991; Erickson, Egeland, & Pianta, 1989; Shields & Cic- chetti, 1998).

An indirect pathway via sensation seeking, though less ro- bust, was also in evidence, connecting adversity to alcohol use and marijuana use. Sensation seeking refers to the tendency to seek out novel or thrilling stimulation (Whiteside et al., 2005). Past studies document the influence of adverse childhood ex- periences on systems associated with reward and self-control. Reward pathways are known to affect sensation-seeking behav- ior and the self-control systems that modulate tendencies to- ward sensation seeking (Steinberg, 2007). It is conceivable that increased exposure to adversity potentiates higher levels of sensation seeking due to a combination of higher inclina- tions to seek excitement coupled with reduced effectiveness in self-regulation (Sinha & Jastreboff, 2013).

Positive urgency was a mediator of the link between child abuse and neglect and alcohol use. This finding is consistent with research on substance use motives that identify enhance- ment motives as important in subclinical levels of alcohol use (Adams et al., 2012). That is, drugs can be used recreationally or viewed as a means to enhance social activities. Thus, in- creased use of drugs in adolescence may occur in the context of positive as well as negative emotions.

Figure 3. Study 2 cross-sectional findings for child abuse and neglect, dimensions of impulsivity, and substance sue outcomes. Standardized parameter estimates shown. Nonsignificant paths not shown for clarity’s sake. Age, gender, and financial stress are used as covariates. *p , .05, **p , .01, ***p , .001.

A. Oshri et al.14

Limitations. Limitations of Study 2 pertain to the use of self- report measures, the cross-sectional collection of data, and sample generalizability. Self-report biases have been dis- cussed above in Study 1. Cross-sectional findings must be interpreted with caution due to the potential for substance use to influence impulsivity. This concern is mitigated to some degree by Study 1, which included a longitudinal de- sign with repeated measures. It is possible that the linkages between the child abuse and neglect and substance use were significant only among two of the five UPPS dimen- sions due to limited power or a lack of variability in substance use among this sample. Finally, because M-Turk does not use random sampling, the correspondence of participants’ demo- graphic characteristics with those of representative US sam- ples is unknown.

General Discussion

Childhood adversity and impulsivity are established predic- tors of substance use in adolescence and young adulthood. In the present study, we tested the hypothesis that the latter may be a mechanism through which the former increases the risk for subsequent substance use. We investigated this hypothesis using two studies. The main aim of Study 1, with a longitudinal, representative data set, was to test the in- direct link between child abuse and neglect and substance use in young adulthood via impulsivity in adolescence. The re- sults supported a model in which child abuse and neglect ex- periences are related to cannabis and cigarette use via impul- sive behavior in adolescence, after controlling for prior impulsivity, substance use, and demographic characteristics. The aim of the cross-sectional study was to investigate the in- direct influence of impulsivity using delayed discounting and trait measures of impulsivity allowing greater assessment specificity. Results confirmed that the indirect paths from early life adversity to substance use were linked via two dis- tinct perspectives on impulsivity: a self-report trait measure and a task-based assessment of delay discounting. We further found that among impulsivity trait subcomponents, negative urgency was the most robust factor connecting adversity to substance use.

The present research suggests that aspects of impulsivity, particularly those implicated in emotion regulation systems, reflect important neurocognitive intermediaries that link ad- verse childhood experiences and subsequent substance use in adulthood. These findings are consistent with theoretical models and recent research with both animals and humans that address neurobiological changes that affect substance use vulnerability. Lovallo (2013) proposed a model whereby early adversity gives rise to a constellation of physiological, cognitive, and affective tendencies that promote impulsive decision making. According to this model, stressful life ex- periences are processed through, and impacted by, regions of the brain that evaluate ongoing events and shape coping behaviors and behavioral responses. Backed primarily by an- imal research, this model suggests that early-life adversity

may reinforce tendencies to discount future rewards. For ex- ample, Lovic et al. (2011) found that maternal separation and social isolation among rat pups led to greater impulsive action and reduced the pups’ behavioral flexibility when they became adults. Animal studies suggest that early-life ad- versity may alter dopamine activity and induce adaptations in regions such as the orbitofrontal cortex and nucleus accum- bens, factors which are known to underlie impulsive behavior and substance use (Hosking & Winstanley, 2011; Winstanley, Olausson, Taylor, & Jentsch, 2010).

Emerging research with humans supports a similar link (Klanecky & McChargue, 2013; Lovallo, 2013; Sinha & Jas- treboff, 2013). The key frontolimbic structures that determine the hypothalamic–pituitary–adrenal axis response to psycho- logical stress include the amygdala (van Marle, Hermans, Qin, & Fernández, 2009), its outputs via the bed nuclei of the stria terminalis (Spencer, Buller, & Day, 2005), the nu- cleus accumbens and the subgenual prefrontal cortex (Mu- hammad, Carroll, & Kolb, 2012), and their collective outputs to the hypothalamus and brainstem (McEwen & Morrison, 2013). These structures are, in turn, regulated by cortisol feedback during states of stress (Lovallo, 2006). The adaptive purpose of this system is understood to be motivating ap- proach and avoidance behaviors. Dysregulation of these fron- tolimbic relationships can result in reduced control over mo- tivated behavior, which compromises affect and behavioral regulation processes associated with vulnerability to addic- tion. In addition, harsh rearing environments influence stress reactivity as measured by hypothalamus–pituitary–adrenal axis and cortisol regulation. Maltreated children have shown dampened diurnal cortisol regulation and increased internal- izing problems, suggestive of serious threat to their neurobi- ological regulation capacities (Cicchetti, Rogosch, & Oshri, 2011). Dysregulation of dopaminergic activity in the nucleus accumbens is putatively associated with reduced experience of reward and potentially greater chronic dysphoria, generat- ing enhanced sensitivity to dopamine released following sub- stance intake (Koob & Kreek, 2007). This research is consis- tent with evidence that stress exposure during development may affect brain structures needed for normal stimulation of cortisol release during stress (De Bellis et al., 1999). Overall, mounting evidence and theoretical conceptualization suggest that early stressful experiences may alter development of crit- ical brain structures involved in downregulating dopamine activity, which can lead individuals exposed to adversity to develop disinhibited behaviors and a behavioral tendency to- ward substance use (Hosking & Winstanley, 2011).

Clinical implications

Accumulating research suggests that delayed reward dis- counting and impulsive personality traits are strongly linked to an individual’s executive functioning (Bobova, Finn, Rick- ert, & Lucas, 2009; Shamosh et al., 2008). Hence, clinical re- searchers have become interested in changing impulsivity- related behaviors including discounting of future rewards

Adversity, impulsivity, and drug use 15

with interventions designed to enhance executive function- ing. As youth who were exposed to early life stress induced by child abuse and neglect appear to be at increased cognitive risk, they may benefit from preventive intervention programs that address cognitive vulnerabilities at early stages of devel- opment. Ultimately, the goal of this research is to better con- ceptualize the etiology of the decision-making impairments observed in youth and young adults exposed to harsh rearing environments and, from there, to develop interventions that will help individuals make more appropriate choices. At present, relatively few evidence-based interventions for mal- treated children and adolescents focus on impaired decision making. Recent research, however, underscores the promise of such approaches. Jankowski et al. (2016) examined the im- pact of participation in multidimensional foster care treatment during preschool to maltreated children who received ser- vices as usual. Children who received multidimensional fos- ter care treatment showed increased response inhibition as early adolescents. Weller, Leve, Kim, Bhimji, and Fisher (2015) found that maltreated foster girls, assigned to risk pre- vention intervention during early adolescence were able to improve their decision making compared to a treatment as usual control. This study was particularly noteworthy as it demonstrated the plasticity of executive functioning training in girls several years after experiencing childhood adversity. Taken together, these studies suggest the importance of ap- proaches that targeted both individual and family-based mo- dalities that support self-regulation. In addition, several such interventions have shown to be effective in reducing risk be- haviors among adults with prefrontal cortex deficits (Bickel et al., 2011; Hewitt, Evans, & Dritschel, 2006). In particular, recent studies show that future thinking reduces the rate of de- lay discounting through a modulation of neural decision- making and episodic future thinking networks (Bickel et al., 2011; Daniel, Stanton, & Epstein, 2013; Peters & Büchel, 2010). Alternatively, given the prominence of negative urgency in the current findings, strategies for im-

proving coping with strong affective states, such as emotion regulation training (Kimbrough, Magyari, Langenberg, Ches- ney, & Berman, 2010; Mendelson et al., 2010), may be of particular benefit for individuals who have experienced early life stress.

Strengths and limitations

The present studies have limitations that should be consid- ered. The use of self-report measures is subject to a number of biases, which have been discussed above. Future studies that incorporate archival records of childhood adversity, ob- servations of impulsivity, as well as additional task-based measures and biomarkers of substance use are needed to va- lidate the present findings. In addition, to assess for adverse rearing environment, child abuse and neglect, was modeled as a latent factor, which was possible due to the signficant covariance between child maltreatment types. However, fu- ture research may contribute to knowledge on the specificity in associations between child maltreatment types and impul- sivity dimensions. Effect sizes observed in the two studies were generally in the small to medium range, suggesting that these influences are present but are by no means the ex- clusive drivers of the link between adversity and substance abuse. Intergenerational continuities, such as behaviors and lifestyles transferred from parent to child (i.e., parental alco- holism), are not specifically examined in the current study, though they may represent pathways through which the devel- opment of substance use behaviors occur (Wickrama, Con- ger, Wallace, & Elder, 1999). These limitations notwithstand- ing, across two studies with diverse methodologies, we documented impulsivity as a potential consequence of ad- verse childhood experiences that increases vulnerability to substance use in adolescence. Our findings also are conso- nant with a growing consensus that impulsivity is a multidi- mensional construct, and that the various impulsivity mea- sures reflect separate underlying processes.

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