Influence of Risk and Protective Factors on Substance Use Outcomes Across Developmental Periods: A Comparison of Youth and Young Adults

Abadi, Melissa H.; Shamblen, Stephen R.; Thompson, Kirsten; Collins, David; Johnson, Knowlton

doi:10.3109/10826084.2011.598598

Cited by 33 publications

(21 citation statements)

References 36 publications

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“…Past research with the SDM also indicates that factors within the community domain are more important at earlier ages, relative to late adolescence (e.g., Cleveland et al, 2008; Harris Abadi et al, 2011). These findings are consistent with the few other studies in the general literature that have examined age differences of community-level factors (Allen et al, 2003; Donovan, 2004; Ferguson & Meehan, 2011).…”

Section: Introductionmentioning

confidence: 99%

Predicting alcohol use across adolescence: Relative strength of individual, family, peer, and contextual risk and protective factors.

Cleveland¹,

Feinberg²,

Jones³

2012

Psychology of Addictive Behaviors

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The current study examined developmental changes in the relative influence of risk and protective factors (RPFs) across individual, family, peer, school, and community domains on adolescent alcohol use. Using longitudinal data from two independent samples, multivariate cross-lagged models were used to estimate the unique influence of each RPF on subsequent changes in recent alcohol use between early to late adolescence. The results supported the hypothesis that the influence of Individual Risk would increase during this developmental period. However, less consistent evidence was found concerning developmental changes among the other domains. Whereas the influence arising from Family Protection diminished during adolescence, the influence of Family Risk, School Protection, and Community Protection did not vary. The influence of Peer Risk showed a nonlinear pattern across adolescence, peaking during the middle adolescent years. The results of this study support a developmental approach to adolescent alcohol use and emphasize the need for prevention strategies that account for these developmental changes.

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Section: Introductionmentioning

confidence: 99%

Predicting alcohol use across adolescence: Relative strength of individual, family, peer, and contextual risk and protective factors.

Cleveland¹,

Feinberg²,

Jones³

2012

Psychology of Addictive Behaviors

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“…Although many factors across levels of social ecology influence substance use (Abadi et al, 2011; Keyes et al, 2011; Sallis et al, 2008; Tang and Orwin, 2009), motives (i.e., reasons for use) are an important individual-level characteristic because they are related to negative consequences (Blevins et al, 2016b; Lee et al, 2009), including developing cannabis use disorders (Benschop et al, 2015; Schlossarek et al, 2016). Motives may change as a result of cannabis interventions; in prior work, reductions in motives (particularly coping-related motives) predicted post-intervention reductions in consumption and consequences (Blevins et al, 2016a), underscoring the need to examine how cannabis-related motives affect consumption.…”

Section: Introductionmentioning

confidence: 99%

Daily associations between cannabis motives and consumption in emerging adults

Bonar

Goldstick

Collins

et al. 2017

Drug and Alcohol Dependence

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Background Increasing rates of cannabis use among emerging adults is a growing public health problem. Intensive longitudinal data can provide information on proximal motives for cannabis use, which can inform interventions to reduce use among emerging adults. Method As part of a larger longitudinal study, patients aged 18–25 years (N=95) recruited from an urban Emergency Department completed daily text message assessments of risk behaviors for 28 days, including daily cannabis quantity and motives. Using a mixed effects linear regression model, we examined the relationships between daily quantity of cannabis consumed and motives (i.e., enhancement, social, conformity, coping, and expansion). Results Participants were, on average, 22.0 years old (SD=2.2); 48.4% were male, 45.3% were African American, and 56.8% received public assistance. Results from the multi-level analysis (clustering day within individual), controlling for gender, race, and receipt of public assistance, indicated daily use of cannabis use for enhancement (β=.27), coping (β=.15), and/or social motives (β=.34) was significantly associated with higher quantities of daily cannabis use; whereas expansion and conformity motives were not. Conclusions Daily data show that emerging adults who use cannabis for enhancement, social, and coping motives reported using greater quantities of cannabis. Future research should examine more comprehensive cannabis motives (e.g., boredom, social anxiety, sleep) and test tailored interventions focusing on alternative cognitive/behavioral strategies to address cannabis motives.

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“…Based on social ecological and resiliency theories (Bronfrenbrenner, 1998; Garmezy, 1991; Rutter, 1987; Stokols et al, 1996), marijuana use during adolescence and emerging adulthood is associated with evolving interactions between individual and social risk and promotive factors that can decrease or accelerate problem trajectories (Abadi et al, 2011; Bernstein et al, 2011; Brown et al, 2008; Cadoret et al, 1995; Cleveland and Wiebe, 2008; Fowler et al, 2007; Henry and Thornberry, 2010; Hussong et al, 2008; Mrug et al, 2010; Wagner, 2008; Windle et al, 2008; Zucker et al, 2000; Zucker et al, 2008). For example, violence is associated with substance use, particularly among those residing in socio-economically disadvantaged communities (Goldstick et al, 2015; Goldstick et al, 2016; Walton et al, 2009; White et al, 2009), likely due to shared risk and promotive factors for some substances (e.g., marijuana), and/or acute pharmacological effects of substances (e.g., alcohol) (Chermack and Giancola, 1997; White et al, 2009).…”

Section: 0 Introductionmentioning

confidence: 99%

“…For example, violence is associated with substance use, particularly among those residing in socio-economically disadvantaged communities (Goldstick et al, 2015; Goldstick et al, 2016; Walton et al, 2009; White et al, 2009), likely due to shared risk and promotive factors for some substances (e.g., marijuana), and/or acute pharmacological effects of substances (e.g., alcohol) (Chermack and Giancola, 1997; White et al, 2009). Although parental influences are important during younger ages, peers are the most robust influence for substance use during the transition to adulthood (Abadi et al, 2011; Allen et al, 2012; Brechwald and Prinstein, 2011; Burk et al, 2012; Chein et al, 2011; Dziak et al, 2014; Simons-Morton and Farhat, 2010; Wolfe et al, 2012), increasing exposure to deviant social contexts and distancing youth from protective influences.…”

Section: 0 Introductionmentioning

confidence: 99%

Marijuana use trajectories among drug-using youth presenting to an urban emergency department: Violence and social influences

Walton

Epstein‐Ngo

Carter

et al. 2017

Drug and Alcohol Dependence

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Aims This paper examined longitudinal marijuana use trajectories among drug-using youth presenting to the ED to inform intervention development. Methods Given interest in substance use and violence, this study oversampled those presenting with assault injuries. Assault-injured youth (ages 14-24) endorsing past 6-month drug use (n=349), and a sex and age proportionally-sampled comparison group (n=250) endorsing drug use, completed a baseline assessment and follow-ups at 6, 12, 18, and 24 months. Latent class trajectory analyses examined days of marijuana use over 2 years. Multinomial regression analyses examined baseline, 12-month and 24-month factors associated with substance use trajectory groups. Results Trajectory analyses identified 5 groups: Low (Low; 28.2%; n=169); Intermittent (INT; 16.2%; n=97); Moderate Decline (MD; 12.0%; n=72); High decline (HD, 13.2%; n=79) and Chronic (C; 30.4%; n=182). At baseline, as compared to the Low group, the other trajectory groups were more likely to be male and have greater levels of physical aggression. At 12- and 24-months, negative and positive peer influences, incarceration and community violence were additional characteristics associated with the greater marijuana use trajectories (as compared to the Low group). Conclusions Interventions for drug-using youth presenting to the urban ED should address peer influences, physical aggression and community violence exposure, given the association between these characteristics and greater marijuana use trajectories.

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Influence of Risk and Protective Factors on Substance Use Outcomes Across Developmental Periods: A Comparison of Youth and Young Adults

Cited by 33 publications

References 36 publications

Predicting alcohol use across adolescence: Relative strength of individual, family, peer, and contextual risk and protective factors.

Predicting alcohol use across adolescence: Relative strength of individual, family, peer, and contextual risk and protective factors.

Daily associations between cannabis motives and consumption in emerging adults

Marijuana use trajectories among drug-using youth presenting to an urban emergency department: Violence and social influences

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