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. Author manuscript; available in PMC: 2022 May 16.
Published in final edited form as: J Adolesc. 2020 Oct 7;85:32–40. doi: 10.1016/j.adolescence.2020.09.002

The role of negative emotional reactivity and neighborhood factors in predicting marijuana use during early adolescence

Rachel M Tache a,*, Jill A Rabinowitz b, Andrew A Gepty a, Sharon F Lambert a, Beth A Reboussin c, Maureen D Reynolds d
PMCID: PMC9109817  NIHMSID: NIHMS1800808  PMID: 33038686

Abstract

Introduction:

Negative emotional reactivity and the neighborhood environment have been individually associated with marijuana use outcomes; however, less is known about whether neighborhood factors differentiate the association between negative emotional reactivity and marijuana use. The present study examined whether neighborhood risk (i.e., neighborhood problems) and protective factors (i.e., neighborhood social cohesion) moderated the relation between negative emotional reactivity and marijuana use during early adolescence.

Methods.

Participants were 775 adolescents (M = 10.95 ± 0.88 years; 69% male; 76% Caucasian), who reported on their past month frequency of marijuana use at Time 1 (when adolescents were 10-12 years old) and Time 2 (when adolescents were 12-14 years old). Mothers reported on neighborhood problems and neighborhood social cohesion at Time 1. Youth reported on their negative emotional reactivity at Time 2.

Results:

Negative binomial regression analyses indicated that neighborhood problems moderated the relationship between negative emotional reactivity and marijuana use. In particular, in the context of low neighborhood problems, individuals with lower negative emotional reactivity were at attenuated risk for marijuana use compared to individuals higher in negative emotional reactivity. In the context of high neighborhood problems, individuals were at heightened risk for marijuana consumption regardless of their negative emotional reactivity levels.

Conclusions:

Findings suggest that individual-level factors alone do not sufficiently account for early marijuana use and that neighborhood problems play a role in risk for or abstention from using marijuana during early adolescence. Implications for prevention and intervention for marijuana use during adolescence are discussed.

Keywords: Marijuana use, Early adolescence, Temperament, Neighborhood

Marijuana use among youth remains a significant public health concern. In particular, marijuana use during early adolescence is linked to a number of adverse educational outcomes (Bray, Zarkin, Ringwalt, & Qi, 2000; Ellickson, Tucker, Klein, & Saner, 2004; Stiby et al., 2014; Williams et al., 2007), psychological health impairments (Degenhardt et al., 2013; Ellickson, Martino, & Collins, 2004; Kosty, Seely, Farmer, Stevens, & Lewinsohn, 2017; Volkow, Baler, Compton, & Weiss, 2014), and illicit drug use (Fergusson, Boden, & Horwood, 2006; Lessem et al., 2006; Lynskey et al., 2003). Elucidating factors that underlie variation in marijuana use during early adolescence carries a renewed urgency given the shifting landscape of marijuana regulations (Roffman, 2016; Salas-Wright & Vaughn, 2017). Changing policies are likely to impact sociocultural norms around marijuana use, which may increase ease of access to marijuana and introduce a wider array of modalities through which youth might consume marijuana. Given the long-term effects of marijuana use during early adolescence and the fact that marijuana may be more accessible to youth, the importance of identifying individual and contextual factors that underpin marijuana use among young people is critical to inform interventions aimed at reducing marijuana use during this developmental period.

1. The role of temperament characteristics in marijuana use behaviors

One individual factor that may influence youths’ engagement in marijuana is temperament, defined as constitutionally based differences in reactivity and regulation that shape how individuals navigate their environments and negotiate risk (Rothbart, 1991). Temperamental differences can be observed early in development and can be targeted for intervention well before youths’ initial exposure to marijuana and onset of use. Although temperament characteristics are relatively enduring, they are not necessarily fixed (Rothbart, 1991). The emotional and cognitive aspects of temperament that impact behavioral responses (Clore & Huntsinger, 2009) are considered malleable by some researchers (Huntsinger, Isbell, & Clore, 2014), suggesting that aspects of temperamental characteristics could be targeted through prevention efforts. For example, youth may be taught emotional and cognitive regulation skills to help offset some features of temperament that confer risk for problem behaviors in some contexts.

Extant research examining the role of temperament factors in marijuana use behavior is limited. One temperamental feature that may be strongly related to marijuana use is negative emotional reactivity, a tendency to experience higher arousal in response to negative emotions and cognitions (Davidson, 1998; Rabinowitz, Osigwe, Byrne, Drabick, & Reynolds, 2016). There is some evidence suggesting that negative emotional reactivity to stimuli may increase during the transition to adolescence (Dahl & Gunnar, 2009) given the vast neurobiological changes that occur during this developmental juncture, making it critical to consider negative emotional reactivity in relation to marijuana use during this developmental period. Negative emotional reactivity may heighten adolescents’ risk for consuming marijuana and be used as a strategy to manage or avoid negative emotions. Youth expressing greater negative emotional reactivity may be more likely to engage in behaviors that are aimed at attenuating negative emotions (Davidson, 1998), and may pursue social situations where there are increased opportunities to use marijuana.

2. Contextualizing associations between temperament factors and marijuana use

The relationship between temperament characteristics, such as negative emotional reactivity, and marijuana use may be moderated by the distal environment, such as the neighborhood. For example, children in lower socioeconomic and higher adversity environments displayed greater stress reactivity (McLaughlin, Conron, Joenen, & Gilman, 2010) and negative affect (Aron, Aron, & Jagiellowicz, 2012) than their peers living in more socioeconomically advantaged contexts. These findings align with ecological models (e.g., Bronfenbrenner, 1994; Sallis, Owen, & Fisher, 2015) suggesting that individual characteristics and subsequent outcomes must be considered in context.

It is well established that the neighborhood environment plays a role in marijuana use outcomes. For example, neighborhood factors (e.g., community cohesion, drug activity and sales in the neighborhood, exposure to community violence, neighborhood collective efficacy, neighborhood disorder) confer risk for or offer protection from substance use behaviors, including marijuana use (Cleveland, Feinberg, Bontempo, & Greenberg, 2008; Fagan, Wright, & Pinchevsky, 2014; Fagan, Wright, & Pinchevsky, 2015; Furr-Holden et al., 2011; Reboussin, Green, Milam, Furr-Holden, & Ialongo, 2014; Wilson, Syme, & Boyce, 2005). This effect may be particularly heightened among youth entering adolescence who may experience newfound independence and spend more time within their neighborhoods relative to childhood (e.g., Cook, Herman, Phillips, & Settersten, 2002).

Research examining whether neighborhood factors influence or moderate the relation between negative emotional reactivity and marijuana use is lacking. One study found that youth higher in sensation seeking, a potential correlate of negative emotional reactivity, engaged in higher levels of marijuana use when the presence of drugs in the neighborhood was high (Andreas & Watson, 2016). Although the studies referenced above examined negative neighborhood features (e.g., disorder, crime, opportunities for drug use) that may confer risk for marijuana use among youth with different temperamental features (e.g., sensation seeking, neurobehavioral disinhibition), similar findings may be expected among youth higher in negative emotional reactivity; indeed, these youth may be especially affected by problems in the neighborhood and be more likely to use marijuana in these contexts. These youth might also experience heightened sensitivity to neighborhood-related stressors as a function of their negative emotional reactivity and use marijuana as a means to cope with challenges.

Although research on whether neighborhood problems impact the relationship between negative emotional reactivity and marijuana use is limited, even less is known about whether positive aspects of the neighborhood environment, such as neighborhood social cohesion, may affect associations between temperament and marijuana use. Neighborhood social cohesion, which refers to attachment to one’s neighborhood and community (Forrest & Kearns, 2001), may have implications for youths’ abilities to acquire marijuana in their neighborhoods and their communities’ attitudes and responses to early adolescent marijuana use. Extant research has found that neighborhood social cohesion predicts prosocial and health promoting behaviors important to adolescent development, including participation in physical activity (e.g., Cradock, Kawachi, Colditz, Gortmaker, & Buka, 2009); condom use (Kerrigan, Witt, Glass, Chung, & Ellen, 2006); sharing, helping, taking care of, and empathizing with other people (Lenzi et al., 2012); and civic engagement (Lenzi, Vieno, Pastore, & Santinello, 2013). These findings demonstrate the protective potential of neighborhood social cohesion in facilitating healthy adolescent development. Residing in neighborhoods higher in social cohesion may particularly benefit youth with higher negative emotional reactivity in terms of their marijuana use. Indeed, increased community supervision of youth and greater consensus among community members regarding appropriate youth behavior may decrease the likelihood of youth obtaining and using marijuana. Neighborhood social cohesion may thus mitigate risk for marijuana use, particularly among youth with higher negative emotional reactivity, necessitating an examination of these relations.

3. The current study

Prior research has examined the individual effects of neighborhood characteristics and temperamental features on marijuana use; yet, little is known about whether neighborhood factors moderate the relation between negative emotional reactivity and marijuana use. Moreover, while a number of studies have examined negative neighborhood factors that contribute to marijuana use (Cleveland et al., 2008; Fagan et al., 2014; Fagan et al., 2015; Furr-Holden et al., 2011; Reboussin et al., 2014; Wilson, Syme, & Boyce, 2005), fewer studies have considered whether neighborhood assets, such as neighborhood social cohesion, buffer risk for marijuana use during early adolescence. Accordingly, the present study examined whether neighborhood problems and social cohesion moderated the association between negative emotional reactivity and marijuana use among youth during early adolescence.

4. Method

Data are drawn from a longitudinal study conducted to examine the etiology of developing substance use disorders (SUD). Biological fathers were recruited through substance dependence and psychiatric treatment programs; courts; and newspaper, television, and radio advertisements. Fathers who had a child aged 10–12 years were eligible to participate and were further screened for inclusion and exclusion criteria. Initial recruitment occurred from 1990 to 2004. Participants were provided with a detailed description of the study before study participation. Written informed consent was obtained from parents and assent was obtained from children. Participants were informed that their privacy was protected by a Certificate of Confidentiality issued to the study from the National Institute on Drug Abuse. Parents and youth were financially compensated after completion of each visit. All study procedures were approved by a University Institutional Review Board. Further information regarding the study design can be found elsewhere (Tarter & Vanyukov, 2001).

4.1. Participants

Mothers and children were assessed at baseline when index children were 10–12 years old (Time 1; M = 10.95 ± 0.88 years; 69% male; 76% Caucasian, 21% African American, 3% biracial). Children and mothers were assessed again approximately 2 years later when the child was 12–14 years old (Time 2; M = 12.99 ± 0.95 years; 72% male). The sample contains more males than females because recruitment of females began four years after the project was underway. The median household income was $27,311 (range = $4999 −$123,128; M = $28,512; SD = $13,521). Demographic characteristics for the study sample can be found in Table 1.

Table 1.

Demographic characteristics of analytic sample.

Characteristic n (%)
Sex
 Male 555 (71.0%)
 Female 225 (29.0%)
Race
 European American 585 (75.5%)
 Ethnic Minority 190 (24.5%)
Father Diagnostic Status
 Fathers with a lifetime SUDa or psychiatric diagnoses 431 (55.6%)
 Fathers without a lifetime SUDa or psychiatric diagnoses 344 (44.4%)
Frequency of Marijuana Use
 0 553 (95.3%)
 1 15 (2.6%)
 2 7 (1.2%)
 3 3 (0.5%)
 4 2 (0.3%)
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a

SUD = substance use disorder.

Participants with missing data (n = 219) differed from participants with complete data (n = 556) in terms of participant sex (χ2 (1) = 4.89, p = .027, φ = 0.079) and father diagnostic status (χ2 (1) = 4.91, p = .027, φ = 0.080) such that participants with missing data were more likely to be male and have a father with a psychiatric or SUD disorder. No other differences on study variables between participants with complete data and those with missing data were found.

4.2. Measures

Participant demographics.

Participant sex and ethnicity information were obtained through caregiver reports at baseline (i.e., when youth were ~10–12 years of age). Father’s diagnostic history was assessed based on the Structured Clinical Interview for DSM-III-R (Spitzer, Williams, Gibbon, & First, 1987, pp. 11–16). Index youth were originally grouped into categories according to their biological father’s lifetime prevalence of mental health disorders: (a) paternal history of SUD or other psychiatric diagnosis not including SUD (55.6%), or (c) no lifetime paternal history of psychiatric diagnosis (44.4%). For the purposes of this study, youth with fathers that had either a lifetime diagnosis of SUD or other psychiatric disorder were coded as 1 and youth with fathers that had no lifetime history of SUD or psychiatric disorder were coded as 0.

Neighborhood problems.

At Time 1, mothers completed the “Your Neighborhood” questionnaire, a 17-item measure developed by the Denver Youth Study (Loeber, Farrington, Stouthamer-Loeber, & Van Kammen, 1998). Caregivers reported on whether a number of negative neighborhood characteristics (e.g., were a problem in their neighborhood) were a problem in their neighborhoods on a scale from 1 = not a problem to 3 = a big problem (α = 0.95). Sample problems included in the questionnaire are “unemployment,” “abandoned houses,” “delinquent gangs,” and “drug use and dealing openly.” Items were summed with higher scores reflecting higher neighborhood problems. This measure has shown strong internal consistency, face validity, and predictive validity regarding children’s behavior problems (McTigue et al., 2015; van der Molen, Hipwell, Vermeiren, & Loeber, 2012).

Neighborhood social cohesion.

At Time 1, mothers reported on neighborhood social cohesion using the Neighborhood Cohesion Instrument (Buckner, 1988). This measure was designed to assess sense of community and quality of social interactions in and level of attraction to the neighborhood. The neighborhood social cohesion measure includes 18 items rated on a scale from 1 = strongly agree to 5 = strongly disagree (α = 0.95). Sample items are “A feeling of fellowship runs deep between me and other people in this neighborhood” and “Living in this neighborhood gives me a sense of community.” Items were summed with higher scores reflecting higher neighborhood social cohesion. The neighborhood social cohesion instrument has demonstrated strong factorial reliability and internal consistency (Li, Hsu, & Hsu, 2011; Wilkinson, 2007).

Negative emotional reactivity.

At Time 2, youth reported on their negative emotional reactivity using the Emotional Susceptibility Scale (Caprara et al., 1982; 1983), a measure designed to assess the ability to tolerate frustration, the experience of distress, and one’s emotional responsiveness to environmental stimuli. This measure includes 40 items rated on a scale from 1 = completely true to 6 = completely false (α = 0.90). Items were summed and higher scores reflect higher negative emotional reactivity. Sample items are “Sometimes I am afraid I will lose control over my feelings; ” “When I am moved, I find it difficult to hold back my tears; ” and “I have often felt upset.” Items were summed with higher scores reflecting higher levels of negative emotional reactivity. The Emotional Susceptibility Scale has demonstrated adequate internal consistency and test-retest reliability (Caprara et al., 1982; 1983).

Frequency of marijuana use.

At Time 2, participants reported on their frequency of marijuana use using the Drug Use Screening Inventory (DUSI; Tarter, 1990). This scale assesses marijuana use in the last month rated on a scale from 0 to 4 (0 = 0 times, 1 = 1–2 times, 2 = 3–9 times, 3 = 10–20 times, 4 = more than 20 times). The DUSI has demonstrated strong internal reliability, split-half reliability, discriminant validity (individuals meeting diagnostic criteria for a psychoactive substance use disorder compared to controls), and predictive validity with substance use disorders in adulthood (Kirisci, Mezzich, & Tarter, 1995; Tarter & Kirisci, 1997; 2001). The distribution of frequency of marijuana use in our sample can be found in Table 1. As noted below, Poisson models were used to model frequency of marijuana use, an approach that has been substantially supported in the literature (e.g., Andreas & Watson, 2016; Atkins, Baldwin, Zheng, Gallop, & Neighbors, 2013; Bandyopadhyay, DeSantis, Korte, & Brady, 2011; Kosterman, Hawkins, Guo, Catalano, & Abbott, 2000; Simons, Neal, & Gaher, 2006; Stautz & Cooper, 2014).

4.3. Statistical analyses

Bivariate correlations were conducted to examine relationships among the predictor and outcome variables using SPSS Version 25 (IBM, 2016). Independent samples t-tests and chi-square analyses were conducted to examine sex differences in negative emotional reactivity and reported marijuana use. The primary analyses were conducted using Mplus Version 8.0 (Muthén & Muthén, 1998-2017). Full Information Maximum Likelihood (FIML) estimation was used to address missing data (Graham, 2009). The demographic and participant variables were coded as follows: (Caucasian = 0, ethnic minority = 1; boys = 0, girls = 1; fathers without a psychiatric or SUD = 0, fathers with a psychiatric or SUD = 1). All continuous predictor variables were z-scored (M = 0; SD = 1).

Frequency of marijuana use is considered count data. Preliminary analyses indicated overdispersion in the distribution of marijuana use frequency, as the variance greatly exceeded the mean. Given the distribution of this variable, we used negative binomial regressions to conduct the regression analyses given that this approach includes an extra parameter that accounts for overdispersion, unlike other methods for analyzing count data (e.g., Poisson regression) (Atkins et al., 2013; Hilbe, 2014).

We controlled for participant sex and ethnicity given that these variables have been associated with differences in marijuana use in adolescence (Blackson & Tarter, 1994, 1999; Hasin et al., 2015; Young et al., 2002). In addition, we included father diagnostic status as a covariate in the analyses given that this was a central component of the recruitment strategy, in addition to numerous studies that point to the importance of father mental health as a predictor of adolescent substance use (Clark, Parker, & Lynch, 1999; Haybech et al., 2005; Moss, Vanyukov, Majumder, Kirisci, & Tarter, 1995). After adjusting for participant sex, ethnicity, and father diagnostic status, we examined (a) the main effects of negative emotional reactivity, and neighborhood factors (i.e., neighborhood problems and social cohesion) on marijuana use, and (b) whether neighborhood factors moderated the relationship between negative emotional reactivity and marijuana use. Given low correlations among neighborhood cohesion and neighborhood problems, we included both neighborhood variables in the same model. The first step included the main effects of the predictor variables (i.e., negative emotional reactivity) and the moderators (i.e., neighborhood problems or cohesion), while controlling for participant characteristics (i.e., sex, ethnicity, and father diagnostic status). The second step included the negative emotional reactivity × neighborhood factors (i.e., neighborhood problems or social cohesion) interaction terms and controlled for participant demographics, negative emotional reactivity, neighborhood cohesion, and neighborhood problems.

For significant interactions, simple slopes were computed to reflect higher and lower neighborhood factors that were at the mean and ±1 SD from the mean of the neighborhood features, respectively (Aiken & West, 1991; Holmbeck, 2002). We examined whether the association between negative emotional reactivity and frequency of marijuana use was significant at high and low levels of the neighborhood factors. Significant interactions were plotted using a publicly available spreadsheet (Dawson, 2014). Ancillary analyses, specifically logistic regressions, were conducted to examine the main effects of the predictors and moderators described above in predicting use of marijuana in the past year with 0 reflecting no use and 1 reflecting any use (see supplementary materials).

5. Results

In terms of sex differences, girls reported higher levels of negative emotional reactivity compared to boys, t(642) = 2.16, p = .031, Cohen’s d = 0.19. No sex differences in marijuana use were observed, F(1, 578) = 0.009, p = .925. Negative emotional reactivity was positively correlated with neighborhood problems, r = 0.18, p < .005, and marijuana use, r = 0.16, p < .005. Neighborhood problems were negatively correlated with neighborhood social cohesion, r = −0.34, p < .005. In addition, there was a non-significant positive correlation between neighborhood problems and marijuana use, r = 0.07, p = .102.

Table 2 provides results of the regression analyses. There were main effects of participant ethnicity (OR = 2.70, 95% CI = 1.06–6.84 p = .037) and negative emotional reactivity (OR = 1.52, 95% CI = 1.02–2.28, p = .038) such that ethnic minority youth and higher negative emotional reactivity was associated with increased risk for using marijuana. A significant main effect was also observed regarding father diagnostic status (OR = 0.44, 95% CI = 0.19–0.98, p = .044) such that children of fathers without a substance use or psychiatric disorder diagnosis were more likely to use marijuana.

Table 2.

Summary of analyses predicting early adolescent marijuana use from neighborhood factors. And negative emotional reactivity.

Model OR (95% CI) p-value
Main Effect Model
 Sex 0.50 (0.20–1.25) .138
 Ethnicity 2.70 (1.06–6.84) .037
 Father diagnostic status 0.43 (0.19–0.98) .044
 Neighborhood cohesion 0.70 (0.44–1.12) .136
 Neighborhood problems 1.47 (0.98–2.21) .059
 Negative emotional reactivity 1.52 (1.02–2.28) .038
Interaction Model a
 Neighborhood cohesion × negative emotional reactivity 0.92 (0.63–1.32) .639
 Neighborhood problems × negative emotional reactivity 0.62 (0.46–0.84) .002
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Note. OR = Odds ratio; CI = Confidence interval.

a

Interaction model included participant sex, age, ethnicity, father diagnostic status, neighborhood cohesion, neighborhood problems, and negative emotional reactivity as covariates.

There was a significant interaction between neighborhood problems and negative emotional reactivity (OR = 0.62, 95% CI = 0.46–0.84, p = .002) (Table 2). Analysis of simple slopes indicated that the association between negative emotional reactivity and marijuana use frequency was significant at low neighborhood problems (B = 1.03, p < .005), but not high neighborhood problems (B = 0.14, p = .477) (Fig. 1). In the context of low neighborhood problems, participants with higher negative emotional reactivity reported more frequent marijuana use than individuals with lower negative emotional reactivity. The neighborhood social cohesion × negative emotional reactivity interaction was not significant, (OR = 0.92, 95% CI = 0.63–1.32, p = .639).

Fig. 1.

Fig. 1.

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Association between emotional reactivity and frequency of marijuana use in the context of. high and low levels of the moderator, neighborhood problems.

6. Discussion

Understanding factors that affect marijuana use outcomes in early adolescence is of great interest given shifting public perceptions and policies around marijuana use in the United States (Roffman, 2016; Salas-Wright & Vaughn, 2017). The consideration of multilevel influences, such as individual (e.g., negative emotional reactivity) and distal contextual factors (e.g., neighborhood problems; neighborhood social cohesion) on marijuana use during adolescence has important implications for initiatives targeting individuals at risk for early marijuana use. Though prior research has indicated that temperamental features (e.g., Lejuez et al., 2014) and aspects of the neighborhood (e.g., Zimmerman & Farrell, 2016) individually predict marijuana use, less is known about whether temperament and neighborhood qualities operate jointly to predict marijuana use behaviors. To address this gap, the present study examined whether neighborhood problems and neighborhood social cohesion conferred risk for marijuana use among youth early in adolescence varying in negative emotional reactivity.

Findings suggest that negative emotional reactivity may be a risk factor for marijuana use in neighborhoods characterized by low problems. These results conflict with some work indicating that certain temperamental features may exacerbate risk for marijuana use in more dangerous neighborhood contexts (Andreas & Watson, 2016). In particular, higher levels of sensation seeking was related to heavier adolescent marijuana use in the context of higher reported neighborhood danger and drug availability (Andreas & Watson, 2016). However, our results are in line with other studies that have indicated that temperament predispositions may heighten risk for other problem behaviors in lower problem neighborhoods (Bush, Lengua, & Colder, 2010).

Whereas low-problem neighborhoods were associated with increased marijuana use among youth with higher levels of negative emotional reactivity, exposure to high problem neighborhoods did not affect the relationship between negative emotional reactivity and marijuana use. Adolescents lower in negative emotional reactivity in high problem neighborhoods may not benefit from the otherwise protective effects of this temperament feature due to the experience of living in a high problem neighborhood characterized by high unemployment and drug sales. Drug dealing in the open, one type of neighborhood problem assessed in the current study, likely increases the likelihood of early exposure and access to marijuana. Poor structural neighborhood quality, such as abandoned houses and vandalism, as well as crime may be linked with low mood and distress (Curry, Lathkin, & Davey-Rothwell, 2008; Leventhal & Brooks-Gunn, 2000a, 2000b; Natsuaki et al., 2007). In these contexts, youth may use marijuana more frequently in direct response to these contextual stressors, regardless of their temperamental features. While constitutionally-based individual differences might have a greater impact in low to average or low problem neighborhoods, the adverse effects of living in a high problem neighborhood may extend to all youth in terms of their marijuana use.

While neighborhood problems moderated the relationship between negative emotional reactivity and marijuana use, neighborhood social cohesion did not. It is possible that youth perceptions of neighborhood social cohesion are more influential in predicting marijuana use outcomes than are maternal reports of neighborhood social cohesion. Future research should incorporate multiple informants of neighborhood factors in conjunction with observational data to best capture experiences in the neighborhood. Additionally, as multi-informant reports may strengthen understanding of youth behaviors that occur in different contexts (De Los Reyes et al., 2015), future studies will benefit from the incorporation of additional informants (e.g., teachers) to assess children’s negative emotional reactivity, neighborhood factors, and marijuana use. It could also be that neighborhood social cohesion may be less relevant in influencing marijuana use among individuals with different levels of negative emotional reactivity. Future research should explore other neighborhood features that may differentially affect youth varying in negative emotional reactivity in terms of their marijuana use.

6.1. Implications

Study findings advance our understanding of factors that contribute to marijuana use during early adolescence, namely that lower neighborhood problems are a key determinant of marijuana use among youth higher in negative emotional reactivity. Youth in high problem neighborhoods are often inundated with contextual risks for substance use (Reboussin et al., 2014) such that individual-level factors alone are likely insufficient to account for early use of marijuana. Meaningful change in marijuana use and negative sequalae must account for structural influences that shape adolescent substance use behaviors. The present research suggests that minimizing neighborhood problems is an important focus, given that elevated levels of neighborhood problems resulted in more frequent marijuana use, regardless of one’s negative emotional reactivity. Interventions should consider the abundant contextual stress shouldered by adolescents in high-problem neighborhoods (Reboussin et al., 2014) and links between neighborhood stress and marijuana use outcomes. It is important to note that low neighborhood problems alone did not eliminate marijuana use. Youth residing in low problem neighborhoods that were higher in negative emotional reactivity reported increased marijuana use. For youth with higher negative emotional reactivity residing in socio-economically advantaged neighborhoods, context-specific intervention targets may be prioritized. For example, social norms that prioritize academic and social status over well-being should be addressed to reduce marijuana use among and youth higher in negative emotional reactivity.

Upon replication of our findings, results have the potential to inform intervention and policy efforts to address marijuana use and related adjustment problems among youth during early adolescence. For example, policies aimed at improving neighborhoods and intervention programs focused on mitigating the adverse effects of negative neighborhood factors are important foci that may improve substance use outcomes through both direct and indirect pathways. Addressing barriers to employment and educational opportunities, and improving the quality of the physical neighborhood environment may be necessary to maximize youths’ outcomes.

6.2. Limitations and future directions

The present study contributes to existing research by examining whether neighborhood factors impact the relation between negative emotional reactivity and marijuana use during early adolescence in a large, diverse sample. In addition to this strength, study limitations should be noted. The generalizability of the findings may be limited due to the predominantly Caucasian composition of the present sample. While father diagnostic status was controlled for, it should be highlighted that 55.6% of the sample included fathers that met diagnostic criteria for a SUD or psychiatric disorder. Future research should replicate these findings in community samples and samples predominantly comprised of youth of color, who disproportionately experience the negative health and legal consequences of substance use (Wilson, 2003). While an understanding of factors that facilitate or prevent marijuana use during early adolescence are important, the role of negative emotional reactivity and neighborhood factors should be examined across adolescence and young adulthood to identify whether the pattern of findings remains consistent across different developmental periods. Further consideration should be given to patterns of marijuana use over time for youth early in adolescence, especially given evidence that trajectories may differ as a function of gender (e.g., Schepis et al., 2011).

Though neighborhood factors individually predict substance use among adolescents (Cambron, Kosterman, Caralano, Guttamannova, & Hawkins, 2018; Meyers & Miller, 2004; Winstanley et al., 2007), it also is important to consider contextual factors (e.g., family, peers) on youth’s substance use behaviors. Future research should also explore whether other temperament characteristics (e. g., hard avoidance, fearfulness, reward persistence) operate differently than negative emotional reactivity in other neighborhood contexts, such as rural environments. Individual characteristics, such as sensation-seeking (e.g., Martin et al., 2002), poor self-control and a tendency toward risk-taking (Wills, Resko, Ainette, & Mendoza, 2004) are risk factors for substance use, which should be explored in the context of varying levels of neighborhood risk and protective factors. The contributions of different temperament characteristics to marijuana use and potential gender differences in these effects also should be explored. In line with ecological models, adolescents’ frequency of marijuana use is likely affected by multiple spheres of influence, necessitating an examination of individual features and micro and macro-level influences that may influence marijuana use across the developmental course.

Supplementary Material

Supplement The role of negative emotional reactivity and neighborhood factors in predicting marijuana use during early adolescence

Acknowledgements

We thank the youth and families who participated in this research, as well as Dr. Ralph Tarter, the Principal Investigator of the Center for Education and Drug Abuse Research. We also thank the National Institute for Drug Abuse for funding support awarded to Dr. Ralph Tarter.

Funding:

This work was supported by the National Institute for Drug Abuse [P50 DA 005605].

Footnotes

Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.adolescence.2020.09.002.

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Supplement The role of negative emotional reactivity and neighborhood factors in predicting marijuana use during early adolescence
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