Unpacking Unexplored Psychological Factors in Alcohol and Substance Use in Gang Members

Abstract

The extant literature has identified that gang involvement is associated with increased substance use frequency and severity. Unfortunately, most gang intervention programs concentrate on minimizing and reducing delinquent behavior and ties to gangs; while neglecting to address substance use among gang members. The current study examines psychopathic traits role in alcohol consumption and substance use among gang members and individuals with a history of gang involvement using the Pathways sample. The study implemented a count mixed effect models to investigate the impact of psychopathic traits on alcohol and substance use in individuals with a history of gang involvement and gang members longitudinally in waves 2, 4, 6, 7, 8, 9, and 10, while controlling for other variables associated with alcohol consumption and substance use frequency. The current study found the impulsivity/irresponsible dimension of psychopathy is associated with consumption of alcohol and substance use longitudinally.

Keywords

gang involvement psychopathic traits chronic substance use alcohol consumption gang intervention

Introduction

Gang involvement is associated with higher rates of illicit substance use, alcohol use, and general risky behavior when compared to the general population and other high-risk groups (Esbensen et al., 2002; Gatti et al., 2005; Gordon et al., 2004; Hall et al., 2006; Sanders, 2017; Swahn et al., 2010; Walker-Barnes & Mason, 2004). Studies comparing gang and non-gang youth found higher lifetime use and chronic use of alcohol, marijuana, and harder illicit drugs (Bjerregaard, 2010; Petering, 2016; Sanders, 2017; Swahn et al., 2010; van Dommenlen-Gonzalez et al., 2015) among gang members. Adolescent substance abuse is associated with the development of substance abuse disorder (SUD), poorer cognitive functioning, abnormal neurodevelopment, sleep disturbances, and risky behaviors (Gray & Squeglia, 2018; Kwon et al., 2019; Sanders et al., 2013; Volkow & Wargo, 2022). However, few interventions have been developed to reduce substance use among active gang members (K. S. Miller et al., 2004) and when considering interventions previous research has found active gang membership reduces the effectiveness of evidence-based interventions (e.g., MST, CBT) (Boxer, 2011; Boxer et al., 2015). Further most intervention programs concentrate on reducing delinquent behavior and terminating gang peer ties, while ignoring substance use which increases the risk of developing substance use disorder and a host of negative outcomes (Arciaga & Gonzalez, 2012; Klein, 2011; van Dommenlen-Gonzalez et al., 2015). Considering the potential negative outcomes (e.g., substance abuse disorder, short/long term delinquency, increase in risky behaviors, poorer quality of life outcomes) associated with adolescent substance use and gang involvement coupled with the fact intervention program effectiveness can be reduced by active gang membership and internalize/externalized symptoms of psychopathology more research on the topic is needed (Kuitunen-Paul et al., 2023). Thus, research should concentrate on comprehending the factors influencing substance use among gang members to improve intervention efforts within the population (Dickson-Gomez et al., 2017).

Most research examining substance use among gang members has concentrated on sociological constructs to explain the relationship, while ignoring psychological constructs. For instance, cultural norms, social disorganization, social learning, social control, social ecology model, multiple marginalization, and strain theories are explanations provided for gang membership and substance use (Bermea et al., 2020; Bishop et al., 2020; Dickson-Gomez et al., 2017; Herd, 2011; Quinn et al., 2019; Sanders, 2012; van Dommelen-Gonzalez et al., 2015). Although some psychological and sociopsychological factors (e.g., impulsivity, sensation seeking, adverse childhood experiences) have received empirical attention regarding substance use among gang members (Moss et al., 2020; Wolff et al., 2020); scant investigation exists examining the role of psychopathic traits have in substance use among individuals with a history of gang membership and current gang members longitudinally. Further, although psychopathy has been assumed to be associated with gang involvement (Sanders, 2017), most empirical investigation has concentrated on sociological constructs and recent empirical focus has begun exploring psychopathy’s role in gang membership. An empirical investigation into the relationship could help improve gang intervention programs by improving the understanding of the potential reasons gang members engage in risky behaviors (Dickson-Gomez et al., 2017).

Psychopathy and Substance Use

Psychopathy is a multi-dimensional personality disorder represented by interpersonal, lifestyle, affective, and antisocial characteristics, and the construct has been extended to adolescents to identify youth that may mature into psychopaths (Salekin & Andershed, 2022; Skeem et al., 2011). In youth, the core traits are representative by grandiose-manipulative (i.e., interpersonal), callous-unemotional (i.e., affective), daring-impulsive (i.e., lifestyle), and conduct disorder (i.e., antisocial behavior) (Salekin & Andershed, 2022; Skeem et al., 2011). The grandiose-manipulative dimension is represented by superficial charm, manipulative, dominant behavior, deceptive, and grandiosity (Cooke et al., 2012; Hare & Neumann, 2009). The callous-unemotional dimension is characterized by low guilt, superficial charm, deceit, disregard for performance, and lack of empathy (Salekin & Andershed, 2022). Finally, the impulsive irresponsibility dimension is represented by violation of rules, criminal versatility, sensation seeking, boredom, and impulsivity (Salekin & Andershed, 2022; Skeem et al., 2011). Although disagreement exists, most researchers suggest that psychopathy in youth is not a unitary construct (Salekin & Andershed, 2022). Psychopathic traits in youth have been associated severity and frequency of substance use (Curtis et al., 2020; Hillege et al., 2010; Poythress et al., 2006; Taylor & Lang, 2006).

The extant literature has observed that psychopathy dimensions are not equally associated with substance use and severity in adolescents. Some studies have found the grandiose-manipulative and callous-unemotional traits are positively associated with substance use frequency and severity (Murrie & Cornell, 2002; O’Neill et al., 2003; Wymbs et al., 2012); while others have not observed a significant relationship (Gillen et al., 2016; Hopley & Brunelle, 2012; Kimonis et al., 2012; J. D. Miller et al., 2011; Sellbom et al., 2017; Waller & Hicks, 2019). Although a large body of evidence has found that the impulsive irresponsibility dimension is positively associated with substance use severity and frequency (Bauer et al., 2011; Colins et al., 2014; Ellingson et al., 2018; Gillen et al., 2016; Hemphälä & Tengström, 2010; Hillege et al., 2010; Nijhof et al., 2011); evidence concerning the distinct contribution of callous unemotional traits have yielded inconclusive findings in adolescence (Anderson et al., 2018; Sakki et al., 2023; Winters et al., 2021). Further, several studies have found the impulsivity irresponsibility dimension mediated the relationship between early life stressors and substance abuse disorders (Doan et al., 2019; Handley et al., 2017; Oshri et al., 2011; Proctor et al., 2017; Wardell et al., 2016). Skeer et al. (2009) in a longitudinal analysis found the impulsive irresponsibility dimension mediated the relationship between substance use over time and experiences early life stressors. The findings observed in adolescents have also been reflected in the adult literature.

In adults, studies found a positive association between cocaine and heroin use and the interpersonal/affective facet (Coid et al., 2009; Vachon et al., 2012; Walsh et al., 2007). While other studies have found that impulsivity mediated the relationship between adverse childhood experiences and alcohol dependence in adulthood (Shin et al., 2015, 2020). Further, other studies have found the irresponsibility impulsivity dimension was associated with an increase in substance use related recidivism and general substance use (Edwards et al., 2021, 2023). However, Colins et al. (2015) did not observed a significant relationship between psychopathic traits and substance use in a sample of adult males. Overall, the most consistent finding suggests that adverse childhood experiences through the irresponsibility impulsivity dimension of psychopathy are associated more substance use and development of substance use disorder in adolescents and adults. One explanation provided is in response to stressors individuals may develop maladaptive personality traits; while a competing explanation suggests the development the psychopathic traits are a temporary adaptive responses to stressors that increase the likelihood of long-term substance use (Kirsch & Lippard, 2022). Considering, that adverse childhood experience has been observed as a salient factor in psychopathic traits, gang membership, couple with the unique relationship gang culture has with substance use and abuse (Sanders, 2017) investigating the relationship longitudinally would improve our understanding of how the constructs interact.

Gang Membership and Substance Use

The extant literature has identified that marijuana and alcohol possess a special relationship with gang culture; while harder illicit substances are less popular (Sanders, 2017). Previous work has identified alcohol and marijuana as the most popular substances gang members use (Fagan, 1993; G. P. Hunt et al., 2002; Mata et al., 2002; Sanders, 2012; Valdez et al., 2006). For gang members, alcohol serves to improve social interactions (e.g., partying), cohesion and solidarity, symbolic gestures (e.g., honor loss gang members, rituals), cope with victimization and criminal behavior and serve as an amplifier for deviant behavior (G. Hunt et al., 2000; G. P. Hunt & Laidler, 2001; Sanders, 2017; Sanders et al., 2010). Further, the racial composition of the gang influences the amount of alcohol consumed and attitudes toward alcohol (Chin, 1990; De La Rosa & Soriano, 1992; Sanders, 2017). Marijuana use is generally accepted within gang culture, and most members report lifetime usage (G. P. Hunt et al., 2002; Moloney et al., 2008; Sanders, 2012; Valdez et al., 2006). Although gang members have higher rates of harder drug use and polydrug use (e.g., heroin, crack, cocaine) compared to the general population, the use of these drugs is lower than alcohol and marijuana (Cepeda et al., 2016; Johnston et al., 2012; Petering, 2016; Sanders, 2012, 2017; Substance Abuse and Mental Health Services Administration [SAMHSA], 2011). Further, hard drug use is stigmatized within the gang culture due to the harmful effects, gang norms, and perceptions of increased vulnerability from drugs; however, evidence shows high use of hard illicit drugs among gang members (Sanders, 2017, 2021). In general, gang membership is associated with increased substance use, and the extant literature has identified several factors associated with substance use in gang membership.

Several factors have also been identified to be associated with the increase and decrease of substance use among gang members. Recent work has found that parental substance use was associated with increased alcohol and marijuana use among gang involved youth (Hoffman et al., 2014; Quinn et al., 2019). Wolff et al. (2020) observed that temperament and current substance use mediates the relationship between adverse childhood experiences (ACEs) and gang involvement. van Dommelen-Gonzalez et al. (2015) found that gang members that had prosocial peers used alcohol and marijuana less frequently while controlling for previously identified factors in substance use. The same study also observed gang members that associated with less future-oriented and prosocial peers increased weekly substance use (van Dommelen-Gonzalez et al., 2015). Bishop et al. (2020) identified four distinct profiles of substance use patterns among gang-involved youth: non-users, past users, casual users, and frequent polysubstance users. The authors found that gang members that did not have positive perceptions of substance use in social environments with minimal substance use and prosocial relationship were more likely to be a part of the non-user category (Bishop et al., 2020). Further, past and casual users had similar demographic and household characteristics profiles; however, casual users’ ecological risk profiles (e.g., family deterrence, access to drugs, more peers that use substances, amount of substance in their neighborhood) are more similar to frequent polysubstance user profiles (Bishop et al., 2020). Finally, polysubstance users most frequently used marijuana and alcohol (Bishop et al., 2020). Most investigation into gang involvement and substance use is cross-sectional and has concentrated on identifying sociological factors to comprehend the relationship between substance use and gang involvement. The goal of the current study is to address these gaps by investigating the role psychopathic facets have on substance use longitudinally among a sample of individuals with a history of gang membership and gang members.

Gang Membership, Psychopathy, and Substance Use

Research examining psychopathy’s relationship with gang membership and gang delinquency have yielded mixed results (Tostlebe & Pyrooz, 2022). Studies concentrating on gang membership have found psychopathy was predictive of gang status (Dmitrieva et al., 2014; Dupéré et al., 2007; Lacourse et al., 2006; Thornton et al., 2015); while other studies have not identified a significant relationship across the psychopathy and gang membership (Ang et al., 2015; Chu et al., 2014; Mallion & Wood, 2018; Valdez et al., 2000). Carson and Ray (2019) observed that both facets of psychopathy were predictive of gang involvement in the Adult Joiner Persister group (i.e., individuals ages 19–23). J. J. Joseph and Rembert (2022) found that psychopathy as a unitary construct was positively associated with gang membership in boys and girls. More recently, J. J. Joseph (2022) investigated which facets of psychopathy were predictive of gang membership to untangle the relationship and found the socially deviant facet was predictive of gang membership in girls, while neither facet was predictive in boys. However, the interpersonal/affective facet almost approached significance being equal to .05 in the analysis and the sex differences did not remain robustly. DeLisi et al. (2019) found that psychopathy rendered the gang-delinquency relationship spurious; while Wolff et al. (2020) was not able to replicate the findings. Most empirical investigation into the psychopathy gang relationship have been cross sectional and have not explored psychopathy’s role in gang membership and behavior longitudinally.

Although overlap exist between psychopathy, gang involvement, substance use (e.g., family adversity, peer delinquency, future orientation, moral disengagement, perceived access to legitimate opportunities), empirical understanding of how the constructs interact remains inconclusive. A theoretical approach that can make sense of overlap between the constructs is Situational Action Theory (SAT). Wikström’s (2014) SAT theory postulates that antisocial behavior is a moral action, and such action is a consequence of the interplay between moral propensities (i.e., individual character or personality features), moral norms of the setting (i.e., the customs or culture of a region or area), and the situation (i.e., the perception-choice process which occurs for an individual within a particular setting and the action (i.e., behavior) following the choice). Considering, the current study’s topic from a SAT perspective it is likely individuals with a history of gang involvement or current gang members higher in callous unemotional traits, more future oriented, residing in socially disorganized neighborhoods with more legitimate opportunities, and more resistant to delinquent peers may be less like to develop substance abuse disorder or engage in substance use long term. Otherwise, individuals with a history of gang involvement or current gang members that are higher in impulsive/irresponsibility dimension of psychopathy, are likely to be less future oriented, less resistant to delinquent peers, residing in social disorganized neighborhoods with fewer legitimate opportunities may be more likely to develop substance abuse disorder or engage in substance use long term.

The Current Study

Most empirical investigations into substance use and abuse among gang members have concentrated on identifying sociological constructs to explain and comprehend the relationship between substance use and gang membership. Although several variables overlap (e.g., delinquent peer association, victimization, delinquency) between substance use, psychopathic traits, and gang membership; scant empirical investigation has examined how the constructs (i.e., psychopathy, gang involvement, substance use) interact longitudinally. Specifically, no study has examined psychopathic facets effect on alcohol and substance use frequency in a sample of individuals with a history of gang involvement and gang members longitudinally. Thus, the current study contributes to understanding potential factors associated with alcohol consumption and substance use longitudinally in a sample of individuals with a history of gang membership and gang members, which can be used to develop targeted intervention strategies toward current and former gang members. In consideration of the findings on psychopathy and substance use in various populations, the current study expects:

1. The callous unemotional dimension will not be significantly associated with alcohol consumption and substance use frequency longitudinally.

2. The impulsive irresponsible dimension will positively be associated with alcohol consumption and substance use frequency longitudinally.

3. The impact of grandiose manipulative dimension will not be associated with be significantly associated with alcohol consumption and substance use frequency longitudinally.

Method

Data

The data utilized to investigate the research question is the Pathways to Desistance dataset (a multi-site, longitudinal study of serious adolescent offenders while they mature into adulthood) (Mulvey, 2013). Ten agencies sponsored data collection to provide policy-makers and justice officials with empirical information on various issues within juvenile justice. The Pathways to Desistance study was initially organized to investigate social and psychological variables related to desistance among serious delinquents. The dataset comprises 700 juvenile offenders from Philadelphia, Pennsylvania, and 654 from Phoenix, Arizona. Adolescents were identified on their adjudication charge, age, and scale of the initial population (Schubert et al., 2004). Following the signing of the appropriate consents, the preliminary meetings occurred in either the youth’s home, an agreed upon location, or the juvenile detention facility. See Mulvey (2004) and Schubert et al. (2004) for an in-depth discussion about the supervising researchers’ methodology and data collection procedures.

For the present study, youth that responded yes to the following 2 items “Have you ever been a member of a gang?” and “Gang membership six months prior” at the baseline are included in the analysis (n = 315), which is 23% of the total pathways sample. Participants that responded yes to either of the question at the baseline were defined as a gang member or individuals with a history of gang membership were extracted from the larger sample. The average age of the gang-involved youth in the sample was 16.02 (1.10), and most of the youth were males (91.1%). Most of the sample was Hispanic (58.4%), followed by Black (22.2%), White (13.7%), and Other (5.7%); along with a mean socio-economic score of 54.29 (12.24) (see Table 1). Attrition for the entire sample was 13.3% (n = 42).

Table 1.

Sample Description.

	%	M	SD	Min	Max
White	13.70
Black	22.20
Hispanic	58.40
Other	5.70
Male	91.10
Female	8.90
Age		16.02	1.104	14	18
SES status		54.29	12.24	26	77

Note. All decimals rounded to the nearest hundredth.

Measures

Dependent Variables

Substance Use Frequency

Substance use frequency is measured by alcohol use frequency, and the number of drugs used in the past 6 months (Chassin et al., 1991; Mulvey, 2013). Participants were asked, “How often have you had alcohol to drink in the past six months?,” which is an item adapted from Chassin’s et al. (1991) substance use and abuse inventory. The number of drugs used is represented by the item “Number of drugs used in the past six months” (Mulvey, 2013). The variables are analyzed in separate models (i.e., alcohol consumption and substance use frequency).

Predictor Variables

Psychopathic Traits

Psychopathic traits are measured by the Youth Psychopathic Traits Inventory (YPI; Andershed et al., 2002), which is a self-report instrument designed to assess psychopathic traits in youth (Mulvey, 2013). The measure taps three dimensions of psychopathy: Grandiose Manipulative Dimension, Callous Unemotional Dimension, and Impulsive Irresponsible Dimension. The scale contains 50 items to which participants respond on a 4-point Likert scale ranging from “Does not apply at all” to “Applies very well.” Several items in the scale are reverse coded so that higher scores indicate more psychopathic characteristics (Andershed et al., 2002; Cauffman et al., 2009; Mulvey, 2013). The self-report nature of the YPI does not require trained interviewers to administer the instrument or official criminal files for review and reduces socially desirable responses due to the neutral or appealing framing of items designed to measure psychopathic traits (Andershed et al., 2002; Cauffman et al., 2009). Further, previous work has found the YPI comparable or superior to other psychopathy assessments (i.e., PCL-YV) (Andershed et al., 2007; Cauffman et al., 2009; Chauhan et al., 2014). Since psychopathy is multi-dimensional construct the grandiose manipulative dimension, callous-unemotional dimension, and impulsive irresponsible dimension (Lilienfeld, 2018) are analyzed separately in the models.

Control Variables

Exposure to Violence

Selner-O’Hagan et al. (1998) Exposure to Violence Inventory (ETV) was used in the sample to investigate the number of violent incidents respondents experienced (Mulvey, 2013). The question from the ETV investigates violent incidents youth have both experienced and observed. Some items ask about the youth’s exposure to incidents of death (e.g., has anyone close to you tried to kill him/herself, has anyone close to you died, have you ever found a dead body, have you ever tried to kill yourself) (Mulvey, 2013). The scale probes about 17 different situations; and items the participant’s respond yes, have a series of follow-up questions regarding the incident. Majority of the items except for rape were restricted to the number of times the event occurred. Participants that responded yes to being a victim of rape or sexual assault are asked four additional questions (i.e., “has it happened more than once?” “relationship of the perpetrator?” “location of the incident?” and “location if other?”) (Mulvey, 2013). For the study violent victimization subscale and witnessed subscale of the exposure to violence scales are used to represent violent victimization and violence witnessed.

Future Orientation

Cauffman and Woolard (1999) used items from (Scheier & Carver, 1985) Life Orientation Task, (Zimbardo, 1990) Time Perspective Scale, and (Strathman et al., 1994) the Future Consequences Scale to develop the Future Outlook Inventory (FOI). The FOI uses Likert scale items (e.g., “I will keep working at difficult boring task if I know that will help me get ahead later”) ranging from 1 to 4 (1 = Never True to 4 = Always True) and higher scores signify more future consideration and planning by the respondent (Mulvey, 2013).

Perceptions of Psychic Rewards of Crime

To operationalize the concept, the personal rewards subscale of the Indices of Personal and Social Costs and Rewards, was adapted for the sample (Mulvey, 2013), which is consistent with previous studies (Lee et al., 2018; Loughran et al., 2012, 2016). The personal rewards subscale includes 7 items with questions like (i.e., “How much of a thrill or rush is it to break into a store or home”) inquiring about the amount of excitement of fun derived from perpetrating delinquent scenarios.

Moral Disengagement

Bandura et al. (1996) Mechanisms of Moral Disengagement tool (MMD) were used to measure a respondent’s inclination to invoke moral disengagement strategies. The MMD scale has 32, 3-point Likert scaled items (e.g., “Disagree” to “Agree”) with higher scores suggesting more moral detachment. The instrument contains eight dimensions: moral justification (e.g., “It is alright to beat someone who bad mouths your family.”), euphemistic language (e.g., “Slapping and shoving someone is just a way of joking.”), advantageous comparison (e.g., “It is okay to insult a classmate because beating him/her is worse.”), displacement of responsibility (e.g., “Kids cannot be blamed for using bad words when all their friends do it”), diffusion of responsibility (e.g., “A kid in a gang should not be blamed for the trouble the gang causes”), distorting consequences (e.g., “Teasing someone does not really hurt them”), attribution of blame (e.g., “If kids fight and misbehave in school it is their teacher’s fault”), and dehumanization (e.g., “Some people deserve to be treated like animals”) (Mulvey, 2013). Following previous scholars’ advice concerning the MMD scale application, the overall score for each wave was used.

Perceived Access to Legitimate Opportunities

The motivation to succeed items are from Eccles et al. (1998) scale, which contains six questions inquiring about the participants perceptions of legitimate opportunities in their neighborhood regarding schooling and work (Thomas et al., 2022) (e.g., “In my neighborhood it is easy for a person to get a good paying job,” “I will never have as much opportunity to succeed as kids from other neighborhoods”); and 2 items on adolescent perceptions regarding academic success (e.g., “How far do you think you will go in school,” “How far would you like to go in school”) (Mulvey, 2013). An overall perceived access to legitimate opportunities score is computed from the 6 items. A higher score indicates more perceived access to legitimate opportunities.

Neighborhood Conditions

The items from Sampson and Raudenbush (1999) self-report measure were adapted to tap into physical and social disorder in a neighborhood (Mulvey, 2013). The scale contains 21 items (e.g., “adults fighting or arguing loudly,” “people using needles or syringes to take drugs”) to which participants respond on a 4-point Likert scale ranging from “Never” to “Often,” with higher scores indicating a greater degree of disorder within the community (Mulvey, 2013).

Association With Deviant Peers

The association with deviant peers is represented by the Peer Delinquency Antisocial behavior subscale from the Rochester Youth Study (Thornberry et al., 1993). The subscale consists of 12 items (e.g., “How many of your friends have sold drugs?” “How many of your friends have suggested you sold drugs?”) on a 5-point Likert scale from “None of them” to “All of them” with higher scores suggesting more association with delinquent peers (Mulvey, 2013).

Peer Delinquency Influence

Peer Delinquency Influence is represented by the Peer Antisocial Influence subscale from the Rochester Youth Study (Thornberry et al., 1993). The subscale consists of 7 items (e.g., “During the recall period how many of your friends have suggested that you should sell drugs?”) on a 5-point Likert scale from “None of them” to “All of them” with higher scores suggesting more peer delinquency influence (Mulvey, 2013).

Resistant to Peer Influence

Resistance to Peer Influence is represented by the Resistance to Peer Influence (Steinberg, 2000) inventory, which was developed to assess the degree adolescents act autonomously in interactions with their peer group (Mulvey, 2013). Participants were presented with two conflicting scenarios (e.g., “Some people go along with their friends just to keep their friends happy” and “Other people refuse to go along with what their friends want to do, even though they know it will make their friends unhappy”) and are asked to choose the scenario which most closely reflects their behavior (Mulvey, 2013). Finally, the participant is asked to rate the degree to which the statement is accurate (i.e. “sort of true” or “really true”). Ten such sequences are presented to the participant, each exploring a different dimension of potential influence: go along with friends, fitting in with friends, changing their mind, knowingly do something wrong, hiding true opinion, breaking the law, changing the way you usually act, taking risks, saying things do not really believe, going against the crowd (Mulvey, 2013).

The overall resistance score was created by assigning each dimension a score from one to four, reflecting the particular combination of answers provided by the subject (Mulvey, 2013). For example, choosing “some people go along with their friends just to keep their friends happy” followed by “really true of me” results in a score of one, while choosing “other people refuse to go along with what their friends want to do” followed by “really true of me” results in a score of four and this is repeated for all ten dimensions (Mulvey, 2013).

Analytic Strategy

The research questions proposed in the study were analyzed with latent variable models (i.e., mixed effect models) due to the equivalency to latent growth models and the count nature of the dependent variables (Grimm & Stegmann, 2019) and were analyzed in R v.4.2.2. The results of the Kolomogorov-Smirnov for alcohol use frequency (KS = 20.729, M/SD = 5.39 (39.92), p < .001), and the number of drugs used in the past 6 months (KS = 3.139, M/SD = 1.66 (1.79), p < .001), which suggest each of the dependent variables are overdispersed, suggesting a negative binomial mixed effects model should be conducted for the dependent variables. The analysis was conducted for waves 3, 5, 7, 8, 9, 10, and 11 of the Pathway’s dataset because each wave was collected annually (see Mulvey, 2004, 2013). For the neighborhood conditions measure, approximately (27.3–39%) was missing at across the various time points within the sample, which resulted in a total of 33% missing for the variable in the total sample. Among the remaining independent, control, and dependent variables, approximately 8 to 10% of the cases were missing at various time points (see Table 2). Missing data were handled with the Expectation Maximization (EM) procedure using the Amelia package in R (see Honaker et al., 2011). Previous work has indicated that the EM procedure is superior to traditional imputation in terms of precision and objectivity and is appropriate for overdispersed count data (Allison, 2002; Enders, 2003; McLachlan, 1997; Walters, 2022).

Table 2.

Independent and Dependent Variables Descriptives.

Wave 1						Wave 2					Wave 3					Wave 4
Variables	N/MI	Mean	SD	Min	Max	N /MI	Mean	SD	Min	Max	N /MI	Mean	SD	Min	Max	N /MI	Mean	SD	Min	Max
Grandiose/manipulative	292/23	40.24	11.23	19	80	290/25	40.71	10.92	20	79	287/28	38.28	10.84	19	77	292/23	36.72	10.59	20	80
Callous unemotional	292/23	34.06	6.62	18	55	290/25	34.39	6.57	15	58	287/28	33.40	6.52	19	57	292/23	32.49	7.01	16	55
Impulsive irresponsibly	292/23	36.62	8.68	15	60	290/25	36.99	7.75	16	57	287/28	34.82	8.41	15	55	292/23	34.58	8.69	15	56
Violence witnessed	292/23	1.29	1.53	0	6	290/25	0.92	1.38	0	7	288/27	0.84	1.35	0	7	294/21	1.25	1.73	0	7
Violent victimization	292/23	0.31	0.71	0	4	290/25	0.19	0.57	0	3	288/27	0.13	0.45	0	3	294/21	0.38	0.82	0	4
Future orientation	292/23	2.43	0.58	1	4	290/25	2.54	0.51	1.38	4	288/27	2.59	0.59	1	4	292/23	2.57	0.55	1.38	4
Personal rewards of crime	292/23	3.06	2.51	0	10	290/25	2.70	2.43	0	10	288/27	2.20	2.31	0	10	294/21	1.99	2.29	0	10
Moral disengagement	292/23	1.65	0.38	1	2.91	290/25	1.60	0.38	1	3	288/27	1.54	0.39	1	2.69	294/21	1.53	0.40	1.03	3
Perceived access to legitimate opportunities	290/25	3.24	0.65	1.50	5	289/26	3.25	0.66	1	5	286/29	3.30	0.63	1	5	294/21	3.30	0.59	1	4.83
Neighborhood conditions	192/123	2.31	0.78	1	4	206/109	2.37	0.79	1	4	201/114	2.41	0.76	1	4	229/86	2.34	0.84	1	4
Delinquent peers	286/29	2.14	0.95	1	5	289/26	1.89	0.85	1	5	274/41	1.69	0.79	1	4.54	290/25	1.89	0.91	1	5
Delinquent peer influence	290/25	1.73	0.88	1	5	289/26	1.65	0.80	1	5	279/36	1.46	0.67	1	3.86	290/25	1.57	0.82	1	5
Resistance to delinquent peer influence	290/25	2.97	0.63	1.10	4	290/25	3.07	0.60	1.40	4	287/28	3.21	0.55	1.60	4	293/22	3.26	0.55	1.50	4
Alcohol consumption	290/25	12.79	32.69	0	420	290/25	16.06	34.15	0	252	287/28	13.78	26.54	0	240	291/24	15.10	25.00	0	210
Substance use	292/23	0.83	1.38	0	9	290/25	.82	1.34	0	9	288/27	.65	1.00	0	7	292/23	.83	1.13	0	6
	Wave 5					Wave 6					Wave 7
Grandiose/manipulative	290/25	37.32	11.37	20	77	285/30	35.45	10.75	20	67	273/42	36.66	10.35	20	76
Callous unemotional	290/25	32.51	7.30	15	57	285/30	32.04	7.47	15	57	273/42	32.66	6.89	15	53
Impulsive irresponsibly	290/25	34.55	9.04	15	60	285/30	34.47	8.88	15	60	273/42	34.05	8.39	15	60
Violence witnessed	290/25	0.99	1.41	0	6	286/29	1.01	1.46	0	6	273/42	1.11	1.59	0	6
Violent victimization	290/25	0.28	0.73	0	4	286/29	0.24	0.67	0	4	273/42	0.26	0.69	0	5
Future orientation	290/25	2.59	0.55	1	2.63	285/30	2.65	0.56	1	4	273/42	2.61	0.58	1	4
Personal rewards of crime	291/24	1.87	2.34	0	10	286/29	1.75	2.26	0	10	274/41	1.85	2.19	0	10
Moral disengagement	290/25	1.49	0.37	1	2.63	285/30	1.46	0.39	1	2.97	273/42	1.45	0.39	1	3
Perceived access to legitimate opportunities	292/23	3.35	0.60	1	5	286/29	3.42	0.64	1	5	274/41	3.30	0.54	2	5
Neighborhood conditions	229/86	2.28	0.81	1	4	218/97	2.13	0.83	1	3.95	197/118	2.22	0.75	1	4
Delinquent peers	288/27	1.77	0.81	1	5	277/38	1.81	0.88	1	5	267/48	1.70	0.81	1	5
delinquent Peer influence	288/27	1.54	0.74	1	5	277/38	1.57	0.82	1	5	267/48	1.43	0.65	1	5
Resistance to delinquent peer influence	290/25	3.33	0.56	1	4	285/30	3.34	0.55	1.2	4	273/42	3.36	0.53	1.60	4
Alcohol consumption	289/26	17.57	28.23	0	180	285/30	19.27	32.33	0	288	272/43	21.38	42.72	0	480
Substance use	289/26	0.79	1.29	0	9	285/30	0.72	1.11	0	9	272/43	0.71	1.13	0	9

Note. All decimals rounded to nearest hundredth. MI = missing.

Model Building Process

The outcome variable for the models were alcohol consumptions and substance use overtime. The unconditional means model simply describes the variation in initial alcohol consumption and substance use scores. Next in the unconditional growth model includes time (i.e., the different time points in the data) as the only predictor to examine within-individual effects (e.g., Level 1). Next, a model was conducted with time, independent variables, and control variables. The final the conditional model included time, independent variables (Grandiose Manipulative Dimension, Callous Unemotional Dimension, and Impulsive Irresponsible Dimension), control variables, and interaction effects to evaluate within and between individual effects. Further, the interaction effects were analyzed to confirm if the pattern of change differed over time for the time variant variables. Time was measured ordinally with the initial assessment deemed 0 and each subsequent year was considered a new timepoint. Considering each variable included in the model was time varying an Adaptive Guass-Hermite Quadrature (AGH) mixed effect model was conducted to deal with issues of autocorrelation. Recently, Nestler (2023) in a simulation study observed the AGH approach was robust against the influence of autocorrelation in the data. For a more detailed review (see Nestler, 2023). Goodness of fit and model selection was determined by Akaike information criteria (AIC), Bayesian information criterion (BIC) statistic, and −2LnLike which were ideal for nested models (Singer & Willett, 2003). Finally, an Analysis of Variance (ANOVA) was conducted to determine the most appropriate model, which are reported in Tables 3 and 4.

Table 3.

Mixed Effect Models for Predictors of Consumption of Alcohol Longitudinally.

Predictors	IRR	CI	p	IRR	CI	p	IRR	CI	p
(Intercept)	10.59	[9.10, 12.32]	<.001	6.57	[4.96, 8.70]	<.001	0.18	[0.04, 0.88]	.034
Time				1.15	[1.07, 1.23]	<.001	1.79	[1.20, 2.65]	.004
Grandiose/Manipulative							1.01	[0.99, 1.03]	.421
Callous unemotional							1.00	[0.97, 1.03]	.958
Impulsive irresponsibly							1.04	[1.01, 1.06]	.009
Violence witnessed							1.17	[1.04, 1.31]	.009
Violent victimization							1.12	[0.87, 1.43]	.374
Future orientation							1.01	[0.76, 1.33]	.958
Personal rewards of crime							1.03	[0.97, 1.10]	.309
Moral disengagement							1.02	[0.67, 1.54]	.932
Perceived access to legitimate opportunities							1.11	[0.87, 1.43]	.389
Neighborhood conditions							0.51	[0.43, 0.62]	<.001
Delinquent peers							1.35	[1.04, 1.74]	.025
Delinquent peer influence							1.66	[1.26, 2.19]	<.001
Resistance to delinquent peer influence							1.39	[1.07, 1.80]	.013
Time × Grandiose/Manipulative							1.00	[0.99, 1.00]	.413
Time × Callous unemotional							1.00	[0.99, 1.01]	.520
Time × Impulsive irresponsibly							1.00	[0.99, 1.00]	.367
Time × Violence witnessed							0.97	[0.94, 1.00]	.048
Time × Violent victimization							1.04	[0.98, 1.11]	.234
Time × Future orientation							1.03	[0.96, 1.10]	.482
Time × Personal rewards of crime							1.00	[0.98, 1.01]	.734
Time × Moral disengagement							0.98	[0.88, 1.08]	.684
Time × Perceived access to legitimate opportunities							0.95	[0.89, 1.02]	.168
Time × Neighborhood conditions							1.00	[0.96, 1.05]	.977
Time × Delinquent peers							1.00	[0.93, 1.07]	.983
Time × Delinquent peer influence							0.99	[0.91, 1.07]	.740
Time × Resistant peer delinquent influence							0.96	[0.90, 1.03]	.253
Random effects
Within person (σ2)	1.55			1.53			1.36
Initial status (τ₀₀)	0.76			1.41			0.23
							1.38
Rate of change (τ₁₁)				0.01			0.01
Covariance (ρ₀₁)				−1.00			−1.00
AIC	14,338			14,325			14,029
BIC	14,355			14,360			14,217
−2 loglikelihood	−7,165.9			−7,156.7			−6,981.7
N	315			315			315
							799
Observations	2,205			2,205			2,205
Marginal R²/Conditional R²	0.000/0.329			0.016/0.218			0.225/0.457

Bolded text are significant p < .0.

Table 4.

Mixed Effect Models for Predictors of Substance Use Longitudinally.

Predictors	IRR	CI	p	IRR	CI	p	IRR	CI	p
(Intercept)	0.55	[0.49, 0.62]	<.001	0.56	[0.48, 0.66]	<.001	0.24	[0.08, 0.72]	.010
Time				0.97	[0.93, 1.01]	.128	1.06	[0.80, 1.41]	.693
Grandiose/Manipulative							1.00	[0.99, 1.01]	.763
Callous unemotional							1.00	[0.97, 1.02]	.675
Impulsive irresponsibly							1.03	[1.01, 1.05]	.002
Violence witnessed							1.08	[1.00, 1.16]	.051
Violent victimization							1.25	[1.09, 1.43]	.001
Future orientation							0.91	[0.74, 1.11]	.334
Personal rewards of crime							1.06	[1.02, 1.10]	.007
Moral disengagement							0.81	[0.61, 1.07]	.145
Perceived access to legitimate opportunities							0.89	0.75, 1.05	.164
Neighborhood conditions							0.88	[0.77, 0.99]	.036
Delinquent peers							1.37	[1.16, 1.62]	<.001
Delinquent peer influence							0.92	[0.78, 1.09]	.343
Resistance to delinquent peer influence							1.13	[0.95, 1.36]	.163
Time × Grandiose/Manipulative							1.00	[1.00, 1.00]	.846
Time × Callous unemotional							1.00	[0.99, 1.01]	.916
Time × Impulsive irresponsibly							1.00	[1.00, 1.00]	.917
Time × Violence witnessed							0.99	[0.97, 1.01]	.504
Time × Violent victimization							0.99	[0.96, 1.03]	.604
Time × Future orientation							1.00	[0.94, 1.05]	.898
Time × Personal rewards of crime							0.99	[0.98, 1.00]	.238
Time × Moral disengagement							1.07	[0.99, 1.15]	.081
Time × Perceived access to legitimate opportunities							0.99	[0.94, 1.04]	.608
Time × Neighborhood conditions							0.99	[0.95, 1.02]	.464
Time × Delinquent peers							0.99	[0.95, 1.04]	.739
Time × Delinquent peer influence							1.04	[0.99, 1.10]	.104
Time × Resistant peer delinquent influence							0.97	[0.93, 1.03]	.324
Random effects
Within person (σ²)	1.12			1.09			1.09
Initial status (τ₀₀)	0.69			0.96			0.05
							0.57
Rate of change (τ₁₁)				0.04			0.02
Covariance (ρ₀₁)				−0.50			−0.56
AIC	5,041.0			5,018.2			4,682.2
BIC	5,058.1			5,052.4			4,870.2
−2 loglikelihood	−2,517.5			−2,503.1			−2,308.1
N	315			315			315
							799
Observations	2,205			2,205			2,205
Marginal R²/Conditional R²	0.000/0.382			0.002/0.443			0.173/0.439

Bolded text are significant p < .0.

Results

A mixed effects models was conducted to examine the relationship between psychopathic traits, (i.e., Grandiose Manipulative Dimension, Callous Unemotional Dimension, and Impulsive Irresponsible Dimension), victimization witnessed, violent victimization, future orientation, personal rewards of crime, moral disengagement, perceived access to legitimate opportunities, neighborhood conditions, association with deviant peers, peer delinquency influence, and resistant to peer influence on number of alcoholic drinks over time. Individuals with a history of gang involvement and gang members that scored higher on the impulsive irresponsible dimension at the start were 4% more likely to consume more alcoholic drinks over time (γ₀₄ = 1.04, p < .01). Individuals with a history of gang involvement and gang members that consumed more alcoholic drinks at the start were 79% more likely to consume more alcoholic drinks over time (γ₀₁ = 1.79, p < .01). Individuals with a history of gang involvement and gang members that witnessed more violent victimization at the start were 17% more likely to consume more alcoholic drinks over time (γ₀₅ = 1.17, p < .01). Individuals with a history of gang involvement and gang members residing in more socially disorganized neighborhoods at the start were 49% less likely to consume more alcoholic drinks over time (γ₁₁ = 0.51, p < .001). Individuals with a history of gang involvement and gang members that associated with more delinquent peers at the start were 35% more likely to likely to consume more alcoholic drinks over time (γ₁₂ = 1.35, p < .05). Individuals with a history of gang involvement and gang members that were more influenced by their more delinquent peers at the start were 66% more likely to consume more alcoholic drinks over time (γ₁₃ = 1.66, p < .001). Individuals with a history of gang involvement and gang members that were more resistant to delinquent peers at the start were 39% more likely to consume more alcoholic drinks over time (γ₁₄ = 1.39, p < .01). Individuals with a history of gang involvement and gang members that witnessed more violent victimization annually had a 3% decrease in alcoholic drinks annually (γ₁₈ = 0.97, p < .05).

A mixed effects models was conducted to examine the relationship between psychopathic traits, (i.e., Grandiose Manipulative Dimension, Callous Unemotional Dimension, and Impulsive Irresponsible Dimension), victimization witnessed, violent victimization, future orientation, personal rewards of crime, moral disengagement, perceived access to legitimate opportunities, neighborhood conditions, association with deviant peers, peer delinquency influence, and resistant to peer influence on number of drugs used over time. Individuals with a history of gang involvement and gang members that scored higher on the impulsive irresponsible dimension at the start were 3% more likely to consume a higher number of drugs over time (γ₀₄ = 1.03, p < .01). Individuals with a history of gang involvement and gang members that experienced more violent victimization at the start were 25% more likely to consume a higher number of drugs over time (γ₀₆ = 1.25, p = .001). Individuals with a history of gang involvement and gang members with higher perceptions of personal rewards for crime at the start were 6% more likely to consume a higher number of drugs over time (γ₀₈ = 1.06, p < .01). Individuals with a history of gang involvement and gang members residing in more socially disorganized neighborhoods at the start were 12% less likely to consume a higher number of drugs over time (γ₁₁ = 0.88, p < .05). Individuals with a history of gang involvement and gang members that associated with more delinquent peers at the start were 37% more likely to likely to consume a higher number of drugs over time (γ₁₂ = 1.37, p < .001).

Discussion

The current study was intended to fill the gaps in the literature regarding gang involvement, psychopathic traits, and substance use longitudinally. Although previous investigation has identified that gang membership and psychopathy separately are associated with an increase in substance use; scant investigation has examined the topic in a sample of individuals with a history of gang involvement and gang members. Further, most investigation has been cross-sectional and has not examined the relationship over an extended period. An improved understanding of the role psychopathy can have on substance use longitudinally can help improve intervention programs designed for gang members and individuals with a history of gang involvement. The current study found support for hypotheses one and three. Specifically, callous-unemotional traits and grandiose manipulative traits were not significantly associated with substance use among individuals with a history of gang involvement and gang members over time. The findings are consistent with the overwhelming number of studies that did not observe a significant relationship between alcohol and substance use with the interpersonal-affective features of psychopathy (Gillen et al., 2016; Hopley & Brunelle, 2012; Kimonis et al., 2012; J. D. Miller et al., 2011; Sellbom et al., 2017; Waller et al., 2020). The findings provide more evidence that the interpersonal/affect dimension of psychopathy may not be related to substance use and alcohol consumption; although a few studies have contradictory findings (O’Neill et al., 2003; Murrie & Cornell, 2002; Walsh et al., 2007; Wymbs et al., 2012). Further, considering previous studies have observed both the callous-unemotional traits and grandiose manipulative traits were associated with gang leadership positions in adulthood (Dmitrieva et al., 2014), it is probable individuals that remained in the gangs long term are less likely to engage in excessive alcohol consumption and substance use long term to remain hypervigilant and maintain their leadership status.

The current study found partial support for hypothesis two; specifically, individuals with a history of gang involvement and gang members that scored higher on the impulsivity/irresponsibility dimension at the start were more likely to consume alcohol and illicit substances over time. However, individuals with a history of gang involvement and gang members that scored higher on the impulsivity/irresponsibility dimension annually were not significantly associated with more consumption of alcohol and substance use annually. In general, the study’s findings are consistent with previous studies that have found the impulsivity/irresponsibility dimension is associated with an increase in substance use and alcohol consumption (Bauer et al., 2011; Colins et al., 2014; Gillen et al., 2016; Hemphälä & Tengström, 2010; Hillege et al., 2010; Kennealy et al., 2007; Kimonis et al., 2012; Nijhof et al., 2011; Sellbom et al., 2017). The findings provide some clarity on the impact of the impulsivity/irresponsibility dimension on long-term alcohol consumption and substance use among individuals with a history of gang involvement and gang members. In the context of the other significant findings, individuals with a history of gang involvement and gang members high in the impulsivity/irresponsibility dimension are probably vulnerable to the influence of delinquent, more manipulative peers regarding substance use and abuse (Curtis et al., 2020). It has been identified that the secondary psychopathic variant experiences victimization, is more emotionally unstable, and is prone to antisocial behavior; therefore, it is likely these youth consume more alcohol and illicit substances longitudinally as a coping mechanism (Gillen et al., 2016; Kimonis et al., 2012; Sellbom et al., 2017). Finally, youth higher on the impulsivity/irresponsibility dimension may become more engrossed in the gang subculture, which has a special relationship with alcohol and marijuana; thus, initial exposure may result in general long-term use (Sanders, 2012, 2017; Valdez et al., 2006).

Treatment and Policy Implications

The findings suggest that treatment inventions targeting gang members should be multifaceted and focus on emotional problems associated with the secondary psychopathic variant to improve and promote positive coping strategies to prevent and reduce alcohol consumption and substance use (Gillen et al., 2016). For instance, gang intervention programs can adopt evidence-based screening devices (e.g., Youth Psychopathic Inventory Short Version [YPI] and Antisocial Processing Screening Device [APSD]) to identify gang involved youth scoring high on the impulsivity/irresponsibility dimension to concentrate on substance abuse and use intervention strategies. Gang program can also adopt Conditional economic incentives (CEI) to reduce substance use through paying gang members for negative drug test and encouraging participating in prosocial environments that do not promote substance use (Dickson-Gomez et al., 2017). Further, gang interventions should acknowledge and consider gang members social environments to help reduce sources of stress and teach effective coping mechanisms (Quinn et al., 2019). Gang programs could shift perceptions of substance use through harm reduction and motivational interviewing (Bishop et al., 2020). Adopting and implementing intervention programs that promote post-traumatic growth and developing prosocial peer connections for victimized and traumatized gang members to reduce their reliance on alcohol and illicit substances (see Berger et al., 2017; Kimonis et al., 2012). For instance, the wrap around method involves an individualized plan for the child and leverages the mental health services available in the child’s immediate area (Underwood & Washington, 2016). Further, policies should redistribute funding to mental health services and be designated to improve services for gang members (see J. Joseph, 2021).

Limitations and Future Research

The study’s findings provide insight into the role facets of psychopathy influence alcohol and illicit substance use longitudinally in a sample of self-identified gang members; however, the study is not without weaknesses. The Pathways sample is comprised of youth involved in serious offenses, which is not representative of most youth involved in the justice system; thus, the findings cannot be generalized to all justice-involved youth that join gangs. Further, the sample demographics (e.g., mixed-sex, racially diverse) did not allow for a comprehensive examination of various types of gangs. Self-report gang identification and substance use have been criticized for validity; however, several studies have verified this technique as an effective method for verifying gang status and illicit substance use behaviors in diverse settings (e.g., Ang et al., 2015; Webb et al., 2006; Williams & Nowatzki, 2005). Further, due to the fluidity of gang membership it likely the participants shifted in and out of gangs during the data collection periods, which is why the participants are consistently referred to as individuals with a history of gang membership and gang membership. By the last wave 50 participants still identified as gang members. Finally, the study relies on self-reported psychopathic traits; however, several studies have validated the instrument (Andershed et al., 2002, 2007; Cauffman et al., 2009).

Despite the limitations, the study relies on empirically validated measures to operationalize the variables tested. The study carefully considers the contribution in relation to previous work on similar topics using the Pathways data (see Waller & Hicks, 2019). The current study uniquely contributes to increasing the understanding between psychopathic traits and alcohol consumption and illicit substance use longitudinally among individuals with a history of gang involvement and gang members longitudinally. The current study does provide information on the effects on the effect of gang involvement, psychopathic traits as it relates to substance use longitudinally. Future research would benefit from considering psychopathic traits’ role in illicit substance use longitudinally in gang samples to better comprehend the factors involved in offending; however, it may be difficult considering how gang membership is fluid. More research must examine the topic to improve and develop evidence-based intervention programs for individuals with a history of gang involvement and gang involved youth. Further, more gang research would generally benefit from examining the role of psychological factors in illicit substance use and alcohol consumption longitudinally.

Footnotes

Declaration of Conflicting Interests

The author declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Justin J. Joseph

Author Biography

Justin J. Joseph is an assistant professor of Criminal Justice at the University of North Alabama. His overall research interest are psychopathy, police & community relations, adult & juvenile gangs, mass shootings, and correctional officer misconduct.

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