Abstract
Objective.
Disinhibitory behavior during childhood and adolescence has been frequently shown to amplify the risk for substance use disorder (SUD) in adulthood. This prospective study examined the hypothesis that poor communication with parents and association with deviant peers comprise an SUD-promoting environtype which catalyzes transition of disinhibitory behavior toward SUD.
Method.
Male (N=499) and female (N=195) youths were tracked from 10-12 to 30 years of age. Path analysis evaluated the patterning of disinhibitory behavior and social environment during childhood on substance use during adolescence, and antisocial personality without co-occurring SUD in early adulthood and subsequently substance use disorder (SUD).
Results.
Disinhibitory behavior (SUD vulnerability) in childhood predicts antisociality without SUD (age 22) that segues to SUD (age 23-30) whereas the environtype (parents and peers) predicts substance use during adolescence which predicts antisocial personality leading to SUD. Antisociality without SUD in early adulthood mediates the association of substance use during adolescence and SUD.
Conclusion.
Disinhibitory behavior and deviance-promoting social environment conjointly promote development of SUD via deviant socialization.
Keywords: adolescence, substance use disorder etiology, parental relationship, peer relationships, substance use, antisocial personality
1. INTRODUCTION
It has been long known that substance use disorder (SUD) in adulthood is frequently preceded during childhood by poor psychological self-regulation, defined as suboptimal cognitive modulation of emotions and behavior during task performance and social interactions (see review in Tarter & Reynolds, 2022). Research aimed at elucidating the role of psychological self-regulation in SUD etiology conducted at the Center for Education and Drug Abuse Research (CEDAR) at the University of Pittsburgh has yielded a continuous trait termed neurobehavior disinhibition (ND). The score on the ND trait encompasses measures of executive cognitive capacity, behavior control and emotion stability (Tarter et al., 2004a). Among preadolescent youths, the score correlates with frontal cortex activity measured by fMRI (McNamee et al., 2008) and performance on the antisaccade task, a sensitive test of prefrontal functioning (Habeych et al., 2005). It also differentiates preadolescent and adolescent youths according to the presence/absence of SUD in biological parents (Tarter et al., 2004b) and predicts SUD between childhood and adulthood (Tarter et al., 2004a). These findings, in aggregate, demonstrate that the ND trait has construct, discriminant and predictive validity for quantifying severity of SUD vulnerability (Mezzich et al., 2007; Kirisci et al., 2004; Tarter et al., 2004a).
A paucity of prospective studies have, however, examined the factors that catalyze the transition from disinhibitory behavior to substance use and subsequently SUD. Within the diathesis-stress framework, complex (polygenic) disorders such that SUD result from the interplay of the social and physical environments and the individual’s biobehavioral vulnerability. Accordingly, it is theorized herein that a social environment facilitating the inculcation of attitudes and behaviors which are discordant with mores and laws comprises an especially important contextual influence on the progression of disinhibitory behavior to SUD. Specifically, non-adherence with societal norms and rules in tandem with poor self-control is hypothesized to bias motivation toward using substances (an illegal behavior during adolescence) as one facet of deviant socialization. In adulthood, substance use is theorized to manifest as antisocial personality that segues to SUD.
The quality of relationship with parents impacts risk for substance use and SUD, particularly in the presence of low psychological self-regulation. For example, difficult temperament in early childhood is associated with negative interactions with parents (Baer et al., 2015; Karreman et al. 2010; Paschall et al., 2015). Its component indicators reflecting poor emotion and behavior self-regulation in toddlers predict substance use and SUD up to two decades later (Horner et al., 2015). During adolescence, youths begin to disengage from parental influence concomitant with increased opportunity to begin substance use. Poor child-parent communication (Cardenas et al., 2022, Hawkins et al., 1992; Luk et al., 2010; Tharp & Noonan, 2012) and mutual dissatisfaction (Tarter et al., 1993) in conjunction with disengaging from the family sphere of influence thus elevated risk for substance use. First exposure to substances most often occurs after an offer from a peer (McIntosh et al., 2003). Hence, a poor relationship with parents facilitates selection of a social environment for friendships that include substance using peers (Kaner et al., 2022). Inasmuch as valuing the opinions of peers over parents increases the likelihood of substance use (Akard et al., 2006), a friendship network marked by substance use and more generally deviancy proneness immerses the child in a social environment that promotes deviant socialization. In effect, family and peer environments are connected, and each facet contributes to the risk for substance use during adolescence (Bahr et al., 2005; Dishion and Tipsord, 2011). The importance of these environments cannot be overemphasized. One study reports that the family and peer environments in fourteen-year-old adolescents account for 77% of variance on frequency of substance use spanning eleven compounds (Walden et al., 2004). Employing a genetically informative experimental design, the authors concluded that “the association among peer deviance, parent-child relationship problems and early substance use is mediated almost entirely by the shared environment” (p.448).
Informed by research demonstrating the integral role of behavior undercontrol (Ersche et al., 2010; Jentsch et al., 2014) and investigations documenting the importance of the parental and peer environments on risk for substance use and SUD, the present longitudinal study examined the relationship between ND (SUD vulnerability phenotype) and these latter two social environments (putative environtype) during childhood on developmental patterning to SUD in adulthood. It is hypothesized that high ND correlates with poor communication with parents and affiliation with delinquent peers during late childhood (age 10-12) and adolescence (age 16), and together foster indifference to societal norms and laws indicated by substance use during adolescence (ages 16 and 19). Substance use as one expression of non-compliance with the law is theorized to advance to antisocial personality without co-occurring SUD (age 22) which segues to SUD (23-30 years of age).
As shown in Figure 1, the theoretical model guiding this study, substance use in middle and late adolescence is hypothesized to mediate the association of predisposing vulnerability (ND) and risk-promoting environtype (quality of communication with parents and affiliation with deviant peers) in childhood and antisociality without SUD in adulthood. Subsequently, antisocial personality is hypothesized to mediate the association between substance use during adolescence and later development of SUD. Thus, whereas many etiological pathways to SUD are possible, this study aims to show that one important and potentially preventable pathway to SUD in early adulthood occurs via the interplay of disinhibitory behavior and parental/peer environments catalyzing non-normative socialization that is first evinced during adolescence as substance use (an illegal behavior) and subsequently antisocial personality.
Figure 1.
Theoretical Model
2. METHODS
2.1. Participants
The participants were enrolled in a longitudinal study conducted by the Center for Drug Abuse Research (CEDAR). The probands were men who qualified for lifetime diagnosis of substance use disorder (SUD) consequent to consumption of illegal drugs (SUD+) (N= 344) and men who had no disorder (SUD−) (N=350). They were recruited using random digit telephone calls, advertisement and referral from clinics. Their children, consisting of 499 boys and 195 girls, were enrolled in this study when they were 10-12 years old and re-evaluated when they attained 16, 19, and 22 years of age. Diagnosis of SUD was formulated between 23-30 years of age. Exclusionary criteria for the children were history of neurological injury that required hospitalization, full-scale IQ below 80, chronic physical disability that would have precluded the child from participating in the protocol, uncorrectable sensory incapacity and psychosis. These factors potentially negatively impact the validity of the data. Separation or divorce of the parents did not exclude their children from the study. Table 1 summarizes the characteristics of the sample. Participants at the baseline evaluation who did not undergo the final follow-up evaluation were not systematically different from retained participants according to personal and demographic characteristics. Although the attrited segment of the baseline sample had significantly lower socioeconomic status and full scale IQ score, both the retained and attrited subjects scored in the average range on these variables.
Table 1.
Participants Retained versus Lost-to-Follow-up at Age 22
Baseline | Retained Age 22 | Lost to Follow- up Age 22 |
Statistic and P value |
|
---|---|---|---|---|
Sex | ||||
Female | 195 | 136 | 59 | X2=3.024 |
Male | 499 | 313 | 186 | p=.08 |
Race | ||||
White | 510 | 336 | 174 | |
Black | 164 | 102 | 62 | X2= 1.587 |
Other | 20 | 11 | 9 | p=.452 |
Dad’s SUD Status1 | ||||
SUD+ | 344 | 217 | 127 | X2=.780 |
SUD− | 350 | 232 | 118 | p=.377 |
M (SD) | M (SD) | M (SD) | ||
Grade in School at Baseline Assessment | 4.64 (1.064) | 4.67 (1.076) | 4.57 (1.040) | F = 1.552, p=.213 |
IQ2 | 1.06.7 (16.063) | 108.68 (16.141) | 103.08 (15.299) | F=19.816, p=<.001 |
SES3 | 40.92 (13.744) | 41.92 (13.880) | 39.08 (13.324) | F=6.816, p=.009 |
SUD+/− refers to presence/absence of substance use disorder in the biological father (proband)
IQ refers to full scale intelligence quotient score on the third edition of the Wechsler Intelligence Scale for Children (WISC-III).
SES denotes socioeconomic status
2.2. Instrumentation
2.2.1. Individual Vulnerability.
The Neurobehavior Disinhibition (ND) Scale administered at 10-12 years of age is a second order factor reflecting the shared variance of first order factors encompassing three dimensions of psychological self-regulation: executive cognitive functioning, behavior control and emotion stability (Tarter et al., 2004a). Previous research has shown that the ND scale has good psychometric properties (Mezzich et al., 2007) and is heuristic for clarifying the etiology of SUD (Kirisci et al., 2004, 2006; Tarter et al., 2004a; Chapman et al., 2007).
2.2.2. Social Environment.
Based on results of many studies showing that the first consumption experience most often occurs in context of an offer of a substance from a friend, and usually in a social setting, it is hypothesized that a weak relationship with parents (who ordinarily provide oversight and protection) allows an opportunity to affiliate with delinquent peers. Accordingly, it is posited that poor communication with parents and delinquency in the friendship network comprise a SUD risk-enhancing environtype during the transition from childhood into adolescence when substances having dependence liability become increasingly available.
The communication subscale of the Youth Attachment to Parents Scale predicts future SUD (Zhai et al, 2014). Alpha coefficients at age 10-12 for child’s report of their relationship with the father and mother are .87 and .87. At age 16, the coefficients are .91 and .85. Examples of items are: “Is your mother/father a good listener?” and “If you were in trouble, could you tell your mother/father?”
The Peer Delinquency Scale (Loeber, 1989), records non-conforming and illegal behavior in the friendship network. Alpha coefficients are .85 and .90 at ages 10-12 and 16. The items document behaviors ranging from status offenses (e.g., “skipping school without an excuse”) to felonies (e.g., “attacked someone with a weapon”). Of the 15 items, 3 query substance use (alcohol, cannabis, and illicit drugs) among peers.
To determine whether the social environment variables constitute an environtype (i.e., a unique etiologically salient social context), the scores on these scales were submitted to exploratory factor analysis. Table 2 presents the factor loadings. A unifactor structure was observed at age 10-12 (Chi-square = .413, df=2, p=.81, CFI/TLI=.99/.99, RMSEA <.001) and age 16 (Chi-square =.07, df=1, p=.786, CFI/TLI/=.984/.951, RMSEA=.108). Moreover, the factor at each age respectively explained 64% and 50% of total variance. These data, showing a unifactor structure, demonstrate that poor relationship with parents and friendships with delinquent peers comprise an environtype. Accordingly, the participant’s environtype factor score was used in the analyses. As shown in Figure 1, high ND vulnerability and high environtype scores are theorized to lead to substance use and subsequently to antisocial personality without concomitant SUD, and afterwards to SUD diagnosis.
Table 2.
Factor Loadings of Communication Scale and Peer Delinquency Scale
Age | Age | |
---|---|---|
10-12 | 16 | |
Communication-Father | .884 | .65 |
Communication-Mother | .811 | .49 |
Peers Delinquency | −.353 | −.357 |
2.2.3. Substance Use.
Polysubstance use is common among adolescents owing largely to a shared genetic liability among the ten SUD categories (Kendler et al., 2003; Tsuang et al., 1998; Vanyukov et al., 2012). Consumption frequency was recorded for twenty substances at 16 and 19 years of age using section 1A of the Drug Use Screening Inventory (DUSI) (Tarter, 1990). The consumption frequency index was derived based on number of consumption events during the past thirty days. Prior research has shown that this measure of substance use frequency at 16 years of age is a predictor of opioid use disorder at 25 years of age (Tarter et al., 2020).
2.2.4. Antisocial Personality.
Antisocial personality disorder (ASPD) is a complex (polygenic) psychiatric disorder resulting from the contribution of many genes interacting with numerous environmental contexts (family, neighborhood, peers, etc.). The ontogenetic trajectory to antisocial personality is marked by non-adherence with societal mores and laws beginning in childhood. Failure to internalize societal norms and rules during child and adolescent development underpins deviant socialization. One marker of deviant socialization is, therefore, regular substance use at 16 and 19 years of age since this is illegal behavior. Hence, it is posited that frequency of substance use predicts the severity of antisocial personality measured as the number of symptoms at 22 years of age reported on the Structured Clinical Interview for DSM-III (SCID) (Spitzer et al., 1990).
2.2.5. Substance Use Disorder (SUD).
Diagnosis of SUD between 23-30 years of age was consensually formulated by a committee consisting of a psychiatrist certified in addiction medicine (chair), another psychiatrist or a psychologist and masters-level research associates who administered the SCID. Consistent with genetic and phenotypic commonality among all SUDs (see Vanyukov & Tarter, 2019), the outcome variable was any SUD.
2.3. Procedure
The participants were instructed during appointment scheduling to abstain from alcohol and drug use (with exception of physician-prescribed medicines) for at least 48 hours prior to the evaluation. Upon arrival at the Center for Education and Drug Abuse Research (CEDAR), the aims and procedures of the project were discussed with the family. CEDAR, a NIDA funded center from 1989-2017 at the University of Pittsburgh, had the mission of elucidating SUD etiology using a prospective paradigm. Consent forms approved by the University of Pittsburgh Institutional Review Board were signed by the parents. The children signed assent forms at ages 10-12, 12-14 and 16 in separate private rooms. No instance of parental coercion, which would disqualify the participant, was detected. Informed consent was provided by the participants at 19 years of age and older. Privacy was additionally protected by a Certificate of Confidentiality issued to CEDAR by the National Institute on Drug Abuse. Breath alcohol and urine drug screens were conducted before implementing the research protocol. A positive result was not detected in any participant. The research protocol was administered in fixed order. Upon completion of the session, the participants were debriefed and compensated for their time at the rate of approximately $10/hour. Meals and travel/parking were also provided.
2.4. Data Analysis
Path analysis was conducted to model the association between individual vulnerability (neurobehavior disinhibition), the putative environtype (parents and peers), substance use, antisocial characteristics, and substance use disorder. Model parameters were estimated using Mplus (Muthén and Muthén, 2017). Mplus uses the full information maximum likelihood estimation method. It provides robust standard error of estimates and chi-square test statistics (if applicable) that are robust to non-normality and non-independence of observations. Model-data goodness-of-fit indices were computed to determine acceptability of the model: χ2 and Akaike, Bayesian and Sample-size adjusted Bayesian information criterion. Mediation analyses were conducted using the method described by Sobel (Sobel, 1982).
Table 3 presents the predictor and outcome scores for the entire sample. Before conducting the path analyses, bivariate correlations were computed. As can be seen in Table 4, all correlations between predictor and outcome variables are significant. Of the 16 correlations, 12 are significant beyond the .001 level of significance.
Table 3.
Scores on predictor variables (ND, family, peer), proximal outcome (SU) and distal (antisocial personality, SUD) outcome variables
M | SD | Range | |
---|---|---|---|
Predictors | |||
Neurobehavior disinhibition (age 10-12) | 50.10 | 10.19 | 27.49 - 94.13 |
Father communication (age 10-12) | 24.47 | 5.73 | 1 – 33 |
Mother communication (age 10-12) | 25.68 | 5.33 | 2 – 33 |
Peer delinquency (age 10-12) | 3.33 | 4.37 | 0 – 37 |
Father communication (age 16) | 19.81 | 10.67 | 3 – 33 |
Mother communication (age 16) | 23.75 | 5.96 | 4 – 33 |
Peer delinquency (age 16) | 8.96 | 7.97 | 0 - 46 |
Proximal Outcome | |||
Substance Use (age 16) | 1.82 | 3.11 | 0 – 10 |
Substance Use (age 19) | 2.77 | 3.46 | 0 - 36 |
Distal Outcomes | |||
Antisocial personality disorder symptoms (age 22) | 0.73 | 1.21 | 0 - 7 |
Substance use disorder (ages 23-30) | N = 203 29.3% |
Table 4.
Correlations between predictor and outcome variables
Outcomes | ||||
---|---|---|---|---|
Predictors | SU (age 16) | SU (age 19) | ASPD symptoms |
SUD |
ND (age 10-12) | .18c | .23c | .35c | .27c |
Communication – Father (age 10-12) | −.09a | −.18c | −.22c | −.13b |
Communication – Mother (age 10-12) | −.10c | −.19c | −.19c | −.10a |
Peer delinquency (age 10-12) | .11a | .17c | .19c | .15c |
p<05
p<.01
p<.001
3. RESULTS
Figure 2 presents the direct paths among the variables. As can be seen, ND at ages 10-12 directly predicts SUD (Beta = .153, p<.001), indicating that the ND trait has predictive validity as a measure of SUD vulnerability. The ND score correlates with the environtype score at age 10-12 (Beta = −.260, p<.001) and 16 years of age (Beta = −.107, p<.01), and predicts severity of antisociality at 22 years of age (Beta=.151, p<.001).
Figure 2.
Results of path analysis
At 16 years of age, a higher environtype severity score is associated with greater substance use frequency (Beta = −.232, p<.001) and at age 19 (Beta=−.077, p<.05). High substance use frequency at 16 years of age predicts high substance use frequency three years later (Beta = −.313, p<.001). In effect, poor communication with parents and affiliation with deviant peers (constituting together the putative SUD environtype) is associated with high substance use frequency (age 16) as well as predicts future high frequency substance use (age 19).
Consistent with illegality of consumption as a facet of antisociality, high frequency of substance use at 16 years of age (Beta = .154, p<.001) and 19 years of age (Beta = .278, p<.001) predicts more severe antisociality which, in turn, predicts SUD (Beta=.459, p<.001) at 22 years of age. Furthermore, substance use frequency at age 19 (Beta = .274, p<.001) forecasts increased risk for SUD.
Mediation analyses additionally support the finding that SUD is the outcome of deviant socialization. Severity of antisociality (age 22) (number of symptoms) mediates the association between ND (ages 10-12) and risk for SUD (ages 23-30) (Beta =.069, z=4.95, p<.001). Environtype (age 10-12) also mediates the association between ND (age 10-12) and antisociality (Beta = .020, z=2.29, p=.02) presaging SUD. Furthermore, antisociality (age 23) mediates the association between substance use frequency (age 19) and SUD (age 23-32) (Beta = .128, z=4.78, p<.001). Lastly, substance use frequency at age 19 mediates the association between substance use frequency at age 16 and severity of antisociality at age 22 (Beta=−.087, z=−4.905, p<.001). In sum, the results indicate that the environtype does not directly predict SUD but as shown in Figure 2, the environtype biases the vulnerable youngster (high ND) toward substance use (illegal behavior) and subsequently antisocial personality that subsequently leads to SUD.
The influence of antisociality in SUD etiology was examined further by testing the analytic model shown in Figure 2 against an identical model that excluded antisocial personality symptoms (age 22). With antisociality included, the sample-size adjusted Bayesian information criterion (BIC) was 12051.94 and when antisociality was excluded, the sample-size BIC was 10275.60. A formal statistical comparison of the two models showed that when antisociality was removed from the model, the sample-size BIC was smaller than when it was included. These analyses indicate that antisociality is not a necessary etiological factor in early age onset SUD; however, it is a salient component of one etiological pathway. These analyses also underscore the heterogeneity of the components of the vulnerability disposition predisposing to SUD, thus antisociality was retained in the final model. Overall, these results demonstrate that the parental and peers environtype during late childhood and mid-adolescence predicts non-adherence with societal mores and rules (underage substance use) which predicts antisocial disposition without SUD leading subsequently to SUD.
4. DISCUSSION
This prospective investigation demonstrated that one outcome of deviant socialization is substance use disorder (SUD). Results of path analysis showed that high neurobehavior disinhibition (SUD vulnerability phenotype) in conjunction with poor communication with parents and affiliation with delinquent peers (environtype) in late childhood (10-12 years of age) and mid-adolescence (age 16) predict substance use frequency which, in turn, predicts severity of antisociality without SUD at 22 years of age. The ND vulnerability phenotype and parent/peer environtype are correlated; however, as can be seen in Figure 2, only ND (age 10-12) directly predicts antisociality (age 22) and SUD (ages 23-30) whereas parent/peers environtype predicts adolescent substance use which predicts antisociality and SUD in adulthood. Antisociality preceding SUD is the outcome, therefore, of both ND vulnerability and environtype featured by non-adherence with societal norms and rules. It is interesting to note, however, that adolescent substance use is predicted only by the environtype. These results concur with Walden et al. (2004) and align with the theory that one variant of SUD, termed ontogenetic addiction, ensues from suboptimal acquisition of psychological self-regulation interacting with an environment that promotes deviant socialization spanning from childhood to adulthood (Tarter & Reynolds, 2022).
These findings do not preclude the importance of additional individual and contextual factors contributing to SUD etiology. The salience of other putative vulnerability (e.g., social cognition, expectancies regarding drug effects) and environment (e.g. neighborhood, school) factors remains to be studied. In addition, the meaning attached to substance consumption in relation to SUD risk requires investigation. For example, substance consumption motivated by desire to alleviate a medical condition (anxiety, pain, insomnia, etc.) may not involve deviancy proneness. Relatedly, it is important to emphasize that social deviancy leading to SUD can be expressed in ways other than just substance use. In particular, risky sexual behavior (Riggs et al., 2013; Mason et al., 2020; Clark et al., 2020; Bohman et al., 2007; Reynolds et al., 2011) creates circumstances for substance consumption that potentiate transitioning to SUD. Lastly, it is important to note that within a sociological framework, antisociality in early adulthood is conceptualized as deviant socialization whereas within a psychiatric framework non-adherence with mores and laws indicate mental illness. All symptoms in the antisocial personality disorder diagnostic category, and most of the symptoms in the SUD category, specify behaviors, not biological disturbance. Considering the strong genetic overlap between antisociality and SUD (Grant et al., 2015; Kendler et al., 2003; Silberg et al., 2003; Muesser et al., 2006) and frequent observation of the progression of childhood conduct disorder to SUD (Myers et al., 1998), it is concluded that SUD is a behavioral outcome of deviant socialization that may or may not include physiological dependence.
Poor parent-child communication correlates with the child’s propensity to affiliate with delinquent peers. This finding has potentially important ramifications for prevention. Previous research, for example, has shown that unreserved communication is the basis of a nurturing relationship which lowers risk for substance use (Luk et al., 2010; Griffin et al., 2011; Lochman & van den Steenhoven, 2002). Open communication with parents also provides the opportunity for the child to internalize normative values, including resistance to using illegal substances (Miller-Day, 2008). Significantly, substance-specific discussion with parents is associated with fewer substance use problems in children (McLaughlin et al., 2016; Mares et al., 2011). These findings, together with results reported by Walden et al. (2004) and the findings reported herein, confirm Patterson’s (1982) theory that deficient parental monitoring bias the child toward friendships which facilitate substance use during adolescence.
Several limitations of the study are noted. Gender comparisons were not conducted owing largely to sample size. Differences in communication style and friendship relationships among males and females may differentially impact socialization and substance use presaging SUD. It is also plausible that mildly deficient psychological self-regulation segues to primarily normative socialization in which substance use is confined to legal drugs (at least for adults) whereas severely impaired self-regulation predisposes to a higher degree of non-compliance with societal norms resulting in a stronger propensity to consume the most negatively sanctioned illegal drugs. Support for distinct etiological patterns to SUD is presented by Krueger et al. (2002) who found that severity of externalizing disorder in childhood covaries with severity of SUD scaled according to legal sanctions. Lastly, recognizing that early age onset substance use heightens risk for SUD, it is important to elucidate the determinants of attitudes, beliefs and values acquired during ontogeny that facilitate motivation to initiate consumption besides those related to deviancy proneness. For instance, high ND score predicts false beliefs about the effects of substance use which in turn increases risk for SUD (Kirisci et al., 2004).
5. CONCLUSION
Disinhibitory behavior during childhood and social environment marked by poor parent-child communication and affiliation with delinquent peers promote deviant socialization leading to SUD. These findings have direct ramifications for SUD prevention. Specifically, enhancing the child’s psychological self-regulation and consolidating an open trusting parent-child relationship are two integral components of multimodal intervention required to bias the ontogenetic trajectory toward socialization anchored to adherence with societal norms and rules, thereby averting adverse outcomes consequent to socially non-normative (and unhealthy) behavior such as SUD.
Highlights.
Poor self-regulation in childhood predicts antisocial personality in adulthood
Poor self-regulation in childhood predicts development of SUD in adulthood
Poor self-regulation in childhood does not predict adolescent substance use
Youth social environment predicts adolescent substance use but not SUD in adulthood
Social environment mediates the relationship between self-regulation and teen SU
Acknowledgements:
This work was supported by the National Institutes of Health, National Institute on Drug Abuse, grant number P50-DA-005605.
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 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.
Declarations of Interest: None
REFERENCES
- Ackard DM, Neumark-Sztainer D, Story M, & Perry C (2006). Parent-child connectedness and behavioral and emotional health among adolescents. American Journal of Preventive Medicine, 30(1):59–66. 10.1016/j.amepre.2005.09.013 [DOI] [PubMed] [Google Scholar]
- Baer J, Schreck M, Althoff RR, Rettew D, Harder V, Ayer L, Albaugh M, Crehan E, Kuny-Slock A, & Hudziak JJ (2015). Child temperament, maternal parenting behavior, and child social functioning. Journal of Child and Family Studies, 24, 1152–1162. 10.1007/s10826-014-9924-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Bahr SJ, Hoffmann JP, & Yang X (2005). Parental and peer influences on the risk of adolescent drug use. Journal of Primary Prevention, 26, 529–551. 10.1007/s10935-005-0014-8. [DOI] [PubMed] [Google Scholar]
- Bohman M (2007). Predisposition to Criminality: Swedish Adoption Studies in Retrospect. 10.1002/9780470514825.ch6. [DOI] [PubMed] [Google Scholar]
- Cardenas LE, Schweer-Collins ML, & Stormshak EA (2022). Parental influences on marijuana use in emerging adulthood. Journal of Family Psychology, 36(2): 170–78. 10.1037/fam0000869 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Chapman K, Tarter R, Kirisci L, & Cornelius M (2007). Childhood Neurobehavior disinhibition amplifies the risk for substance use disorder: Interaction of parental history and prenatal alcohol exposure. Journal of Developmental Behavioral Pediatrics, 28, 219–224. 10.1097/DBP.0b013e3180327907 [DOI] [PubMed] [Google Scholar]
- Clark DA, Donnellan MB, Durbin CE, Nuttall AK, Hicks BM, & Robins RW (2020). Sex, drugs, and early emerging risk: Examining the association between sexual debut and substance use across adolescence. PLoS ONE, 15(2): e0228432. 10.1371/journal.pone.0228432 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Dishion TJ, & Tipsord JM (2011). Peer contagion in child and adolescent social and emotional development. Annual Review of Psychology, 62, 189–214. 10.1146/annurev.psych.093008.100412 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Ersche KD, Turton AJ, Pradhan S, Bullmore ET, & Robbins TW (2010). Drug addiction endophenotypes: Impulsive versus sensation seeking personality traits. Biological Psychiatry, 68, 770–773. 10.1016/j.biopsych.2010.06.015 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Grant JD, Lynskey MT, Madden PAF, Nelson EC, Few LR, Bucholz KK, Statham DJ, Martin NG, Heath AC, & Agrawal A (2015). The role of conduct disorder in the relationship between alcohol, nicotine and cannabis use disorders. Psychological Medicine, 45(16), 3505–3515. 10.1017/S0033291715001518 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Griffin KW, Samuolis J, & Williams C (2011). Efficacy of a self-administered home-based parent intervention on parenting behaviors for preventing adolescent substance use. Journal of Child and Family Studies, 20(3):319–325. 10.1007/s10826-010-9395-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Habeych M, Sclabassi R, Charles P, Kirisci L, & Tarter R (2005). Association between parental substance use disorder, P300 amplitude and neurobehavior disinhibition in pre-teen boys at high risk for substance use disorder. Psychology of Addictive Behaviors, 19, 123–130. 10.1037/0893-164X.19.2.123 [DOI] [PubMed] [Google Scholar]
- Hawkins JD, Catalano RF, & Miller JY (1992). Risk and protective factors for alcohol and other drug problems in adolescence and early adulthood: implications for substance abuse prevention. Psychological Bulletin, 112(1):64–105. 10.1037/0033-2909.112.1.64. [DOI] [PubMed] [Google Scholar]
- Horner M, Braxter B, Kirisci L, & Tarter R (2015). Temperament disturbances in infancy progress to substance sue disorder 20 years later. Personality and Individual Differences, 82, 96–101. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Jentsch JD, Ashenhurst JR, Cervantes MC, Groman SM, James AS, & Pennington ZT (2014). Dissecting impulsivity and its relationships to drug addictions. Annals of the New York Academy of Sciences, 1327, 1–26. 10.1111/nyas.12388 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Kaner E, Islam S, & Lipperman-Kreda S (2022). Adolescent alcohol initiation: Context of close friendships and the role of trust. Drug and Alcohol Dependence, 237, 109515. 10.1016/j.drugalcdep.2022.109515 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Karreman A, deHaas S, van Tuijl C, van Aken MAG, & Deković M (2010). Relations among temperament, parenting and problem behavior in young children. Infant Behavior and Development, 33(1), 39–49. 10.1016/j.infbeh.2009.10.008 [DOI] [PubMed] [Google Scholar]
- Kendler KS, Jacobson KC, Prescott CA, & Neale MC (2003). Specificity of genetic and environmental risk factors for use and abuse/dependence of cannabis, cocaine, hallucinogens, sedatives, stimulants, and opiates in male twins. American Journal of Psychiatry, 160(4):687–95. doi: 10.1176/appi.ajp.160.4.687. 10.1176/appi.ajp.160.4.687 [DOI] [PubMed] [Google Scholar]
- Kirisci L, Tarter R, Vanyukov M, & Reynolds M (2006). Individual differences in childhood neurobehavior disinhibition predict decision to desist substance use during adolescence and substance use disorder in young adulthood: A prospective study. Addictive Behaviors, 31, 686–696. 10.1016/j.addbeh.2005.05.049 [DOI] [PubMed] [Google Scholar]
- Kirisci L, Tarter R, Vanyukov M, Reynolds M, & Habeych M (2004). Relation between cognitive distortions and neurobehavior disinhibition on the development of substance use during adolescence and substance use disorder by young adulthood: a prospective study. Drug and Alcohol Dependence, 76(2), 125–133. 10.1016/j.drugalcdep.2004.04.015 [DOI] [PubMed] [Google Scholar]
- Krueger RF, Hicks BM, Patrick CJ, Carlson SR, Iacono WG, & (2002). McGue, M. Etiologic connections among substance dependence, antisocial behavior, and personality: modeling the externalizing spectrum. Journal of Abnormal Psychology, 111(3), 411–24. 10.1037/0021-843X.111.3.411 [DOI] [PubMed] [Google Scholar]
- Lochman JE, & van den Steenhoven A (2002). Family-based approaches to substance abuse prevention. Journal of Primary Prevention, 23:49–114. 10.1023/A:1016591216363 [DOI] [Google Scholar]
- Loeber R (1989) Peer Delinquency Scale, Pittsburgh Youth Study, Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania. [Google Scholar]
- Luk JW, Farhat T, Iannotti RJ, & Simons-Morton BG (2010). Parent-child communication and substance use among adolescents: do father and mother communication play a different role for sons and daughters? Addictive Behaviors, 35(5):426–31. 10.1016/j.addbeh.2009.12.009 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Mares SH, van der Vorst H, Engels RC, & Lichtwarck-Aschoff A (2011). Parental alcohol use, alcohol-related problems, and alcohol-specific attitudes, alcohol-specific communication, and adolescent excessive alcohol use and alcohol-related problems: An indirect path model. Addictive Behaviors, 36(3):209–16. 10.1016/j.addbeh.2010.10.013 [DOI] [PubMed] [Google Scholar]
- Mason M, Mennis J, Moore M, & Brown A (2019). The role of sex, executive functioning, and perceptions of safety on urban adolescent substance use. Addiction Research & Theory, 28(2), 144–151. 10.1080/16066359.2019.1601708 [DOI] [Google Scholar]
- Mcintosh J, Macdonald F, & Mckeganey N (2003). The initial use of drugs in a sample of pre-teenage schoolchildren: the role of choice, pressure and influence. Drugs: Education, Prevention and Policy, 10, 1–3. 10.1080/0968763021000061092. [DOI] [Google Scholar]
- McLaughlin A, Campbell A, & McColgan M (2016). adolescent substance use in the context of the family: a qualitative study of young people's views on parent-child attachments, parenting style and parental substance use. Substance Use and Misuse, 51(14):1846–55. 10.1080/10826084.2016.1197941 [DOI] [PubMed] [Google Scholar]
- McNamee R, Dunfee K, Luna B, Clark D, Eddy W, & Tarter R (2008). Brain activation, response inhibition and increased risk for substance use disorder. Alcoholism: Clinical and Experimental Research, 32(3), 405–413. 10.1111/j.1530-0277.2007.00604.x [DOI] [PubMed] [Google Scholar]
- Mezzich A, Tarter R, Feske U, Kirisci L, McNamee R, & Day B (2007). Assessment of risk for substance use disorder consequent to consumption of illegal drugs: Psychometric validation of the neurobehavior disinhibition trait. Psychology of Addictive Behaviors, 21(4), 508–515. 10.1037/0893-164X.21.4.508 [DOI] [PubMed] [Google Scholar]
- Miller-Day M (2008). Talking to Youth about drugs: what do late adolescents say about parental strategies?. Family Relations, 57(1):1–12. 10.1111/j.1741-3729.2007.00478.x [DOI] [Google Scholar]
- Mueser KT, Crocker AG, Frisman LB, Drake RE, Covell NH, & Essock SM (2006). Conduct disorder and antisocial personality disorder in persons with severe psychiatric and substance use disorders. Schizophrenia Bulletin, 32(4), 626–636. 10.1093/schbul/sbj068 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Muthen LK, & Muthen BO (2017). MPlus User’s Guide Fourth Edition. Loa Angeles, CA: Muthen and Muthen. [Google Scholar]
- Myers MG, Stewart DG, & Brown SA (1998). Progression from conduct disorder to antisocial personality disorder following treatment for adolescent substance abuse. American Journal of Psychiatry, 155(4), 479–485. 10.1176/ajp.155.4.479 [DOI] [PubMed] [Google Scholar]
- Paschall KW, Gonzalez H, Mortensen JAK, Barnett MA, & Mastergeorge AM (2015). Children’s negative emotionality moderates influence of parenting styles on preschool classroom adjustment. Journal of Applied Developmental Psychology, 39, 1–13. 10.1016/j.appdev.2015.04.009 [DOI] [Google Scholar]
- Patterson GR (1982). A social learning approach to family intervention: Vol. 3. Coercive family process. Eugene, OR: Castalia. [Google Scholar]
- Razzino BE, Ribordy SC, Grant K, Ferrari JR, Bowden BS, & Zeisz J (2004). Gender-related processes and drug use: self-expression with parents, peer group selection, and achievement motivation. Adolescence, 39(153):167–77. [PubMed] [Google Scholar]
- Reynolds MD, Tarter RE, Kirisci L, Clark DB (2011). Marijuana but not alcohol use during adolescence mediates the association between transmissible risk for substance use disorder and number of lifetime violent offenses. Journal of Criminal Justice, 39: 218–223. 10.1016/j.jcrimjus.2011.02.002 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Riggs NR, Tate EB, Ridenour T, Reynolds M, Zhai ZW, Vanyukov M & Tarter R (2013). Longitudinal associations from neurobehavioral disinhibition to risky sexual behavior during adolescence: Direct and mediated effects through heavy alcohol consumption. Journal of Adolescent Health, 53: 465–70. 10.1016/j.jadohealth.2013.05.017 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Silberg J, Rutter M, D’Onofrio B, & Eaves L (2003). Genetic and environmental risk factors in adolescent substance use. Journal of Child Psychology and Psychiatry, 44(5), 664–676. 10.1111/1469-7610.00153 [DOI] [PubMed] [Google Scholar]
- Sobel ME (1982). Asymptomatic confidence intervals for indirect effects in structural equation models. In Leinhardt S (ed.), Sociological Methodology. Washington, DC: American Sociological Association, 290–312. [Google Scholar]
- Spitzer RL, Williams JBW, Gibbon M, & First MB (1990). SCID user's guide for the Structured Clinical Interview for DSM-III-R. Washington, DC: American Psychiatric Press, Inc. [Google Scholar]
- Tarter R (1990). Evaluation and treatment of adolescent substance abuse: A decision tree method. American Journal of Drug and Alcohol Abuse, 16, 1–46. [DOI] [PubMed] [Google Scholar]
- Tarter R, Blackson T, Martin C, Seilhamer R, Pelham W, & Loeber R (1993). Mutual dissatisfaction between mother and son in substance abuse and normal families: Association with child behavior problems. The American Journal on Addictions, 2(2), 1–10. [Google Scholar]
- Tarter R, Kirisci L, Cochran G, Seybert A, Reynolds M, & Vanyukov M (2020). Forecasting opioid use disorder at 25 years of age in 16-year old adolescents. The Journal of Pediatrics, 225, 207–213e1. 10.1016/j.jpeds.2020.07.025 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Tarter R, Kirisci L, Habeych M, Reynolds M, & Vanyukov M (2004a). Neurobehavior disinhibition in childhood predisposes boys to substance use disorder by young adulthood: Direct and mediated etiologic pathways. Drug and Alcohol Dependence, 73(2), 121–132. 10.1016/j.drugalcdep.2003.07.004 [DOI] [PubMed] [Google Scholar]
- Tarter R, Kirisci L, Reynolds M, & Mezzich A (2004b). Impact of neurobehavior disinhibition and parental history of substance use disorder on offspring’s suicide propensity. Drug and Alcohol Dependence, 76(Supplement), S45–S52. 10.1016/j.drugalcdep.2004.08.006 [DOI] [PubMed] [Google Scholar]
- Tarter RE, Reynolds MD (2022). Psychological Antecedents and Correlates of Substance Use and Addiction. In: Vanyukov MM (ed.) Genetics of Substance Use. Springer, Cham. 10.1007/978-3-030-95350-8_3 [DOI] [Google Scholar]
- Tharp AT, & Noonan RK (2012). Associations between three characteristics of parent-youth relationships, youth substance use, and dating attitudes. Health Promotion Practice, 13(4):515–23. 10.1177/1524839910386220 [DOI] [PubMed] [Google Scholar]
- Tsuang MT, Lyons MJ, Meyer JM, Doyle T, Eisen SA, Goldberg J, True W, Lin N, Toomey R, & Eaves L (1998). Co-occurrence of abuse of different drugs in men: the role of drug-specific and shared vulnerabilities. Archives of General Psychiatry, 55(11):967–72. 10.1001/archpsyc.55.11.967. [DOI] [PubMed] [Google Scholar]
- Vanyukov M, Tarter R, Kirillova G, Kirisci L, Reynolds M, Kreek M, Conway K, Maher B, Iacono W, Brent L, Neale M, Clark D, & Ridenour T (2012). Common liability to addiction and “gateway hypothesis”. Theoretical, empirical and evolutionary perspective. Drug and Alcohol Dependence, 123, S3–S17. 10.1016/j.drugalcdep.2011.12.018 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Vanyukov MM, Tarter RE (2019). Genetics and Epigenetics of Substance Use. In: Sloboda Z, Petras H, Robertson E, Hingson R (eds) Prevention of Substance Use. Advances in Prevention Science. Springer, Cham, 10.1007/978-3-030-00627-3_4 [DOI] [Google Scholar]
- Walden B, McGue M, Iacono WG, Burt SA, & Elkins I (2004). Identifying shared environmental contributions to early substance use: the respective roles and peers and parents. Journal of Abnormal Psychology, 113(3), 440–450. 10.1037/0021-843X.113.3.440 [DOI] [PubMed] [Google Scholar]
- Zhai ZW, Kirisci L, Tarter RE, & Ridenour TA (2014). Psychological dysregulation during adolescence mediates the association of parent-child attachment in childhood and substance use disorder in adulthood. American Journal of Drug and Alcohol Abuse, 40(1), 67–74. 10.3109/00952990.2013.848876 [DOI] [PMC free article] [PubMed] [Google Scholar]