Hostname: page-component-586b7cd67f-2plfb Total loading time: 0 Render date: 2024-11-25T15:05:34.546Z Has data issue: false hasContentIssue false

Personality-specific pathways from bullying victimization to adolescent alcohol use: a multilevel longitudinal moderated mediation analysis

Published online by Cambridge University Press:  07 February 2022

Flavie M. Laroque*
Affiliation:
Department of Psychiatry and Addiction, University of Montreal, and CHU Ste Justine Research Center, Montreal, QC, Canada
Elroy Boers
Affiliation:
Department of Psychiatry and Addiction, University of Montreal, and CHU Ste Justine Research Center, Montreal, QC, Canada
Mohammad H. Afzali
Affiliation:
Department of Psychiatry and Addiction, University of Montreal, and CHU Ste Justine Research Center, Montreal, QC, Canada
Patricia J. Conrod
Affiliation:
Department of Psychiatry and Addiction, University of Montreal, and CHU Ste Justine Research Center, Montreal, QC, Canada
*
Corresponding author: Flavie M. Laroque, email: [email protected]
Rights & Permissions [Opens in a new window]

Abstract

Bullying victimization is common in adolescence and has been associated with a broad variety of psychopathology and alcohol use. The present study assessed time-varying associations between bullying victimization and alcohol use through internalizing and externalizing symptoms and whether this indirect association throughout time is moderated by personality. This 5-year longitudinal study (3,800 grade 7 adolescents) used Bayesian multilevel moderated mediation models: independent variable was bullying victimization; moderators were four personality dimensions (anxiety sensitivity, hopelessness, impulsivity, and sensation seeking); internalizing symptoms (anxiety, depressive symptoms) and externalizing symptoms (conduct, hyperactivity problems) were the mediators; and alcohol use, the outcome. Results indicated significant between, within, and lagged effects on alcohol use through internalizing and externalizing symptoms. There were significant between and within effects on alcohol use through internalizing symptoms for adolescents with high anxiety sensitivity and hopelessness, and significant between, within, and lagged effects on alcohol use through externalizing symptoms for adolescents with high impulsivity and sensation seeking. These findings implicate two risk pathways that account for how bullying victimization enhances alcohol use risk and emphasize the importance of personality profiles that can shape the immediate and long-term consequences of victimization.

Type
Regular Article
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
© The Author(s), 2022. Published by Cambridge University Press

Introduction

Bullying victimization and alcohol use

Bullying victimization is defined as being a target of repeated bullying in a physical, verbal, or psychological way by perpetrators who intend to cause harm, and is based on an imbalance of power (Olweus, Reference Olweus1993). Major public concerns have been raised about the impact of bullying victimization on short-term and long-term mental health (Evans-Lacko et al., Reference Evans-Lacko, Takizawa, Brimblecombe, King, Knapp and Maughan2017; van Geel, Vedder, & Tanilon, Reference van Geel, Vedder and Tanilon2014; Woo et al., Reference Woo, Chang, Hong, Lee, Hahm, Cho and Kim2019). One particular concern is the effect of bullying victimization on adolescent alcohol use. Adolescence is a period of physical and psychological transition, during which adolescents are vulnerable to the effects of alcohol use, the most commonly used substance during this period of time (Johnston et al., Reference Johnston, Miech, O’Malley, Bachman, Schulenberg and Patrick2018). Early use of alcohol is associated with physical injury and risky health behaviors (Hanna et al., Reference Hanna, Yi, Dufour and Whitmore2001). Its harmful effect on health may also interfere with brain development (Hill et al., Reference Hill, White, Chung, Hawkins and Catalano2000). The association between bullying victimization and alcohol use has been investigated; however, there are three noteworthy key gaps in the relevant literature: (1) the use of longitudinal and sensitive developmental designs that differentiate common vulnerability from concurrent and longitudinal relationships (overall, short-term; long-term) to clarify the nature of temporal precedence in these associations, (2) mechanisms by which long-term relationships are maintained (paths) and (3) specificity of the relationships. This study aimed to address these three gaps in the literature using an exceptional database that allows for sensitive analysis of time-dependent variations in victimization, mental health and substance use throughout the course of adolescence.

Effect of bullying victimization on alcohol use

Associations between bullying victimization and alcohol use have been studied extensively, as summarized in a systematic review by Maniglio et al. (Reference Maniglio2017) and a meta-analysis by Moore et al. (Reference Moore, Norman, Suetani, Thomas, Sly and Scott2017). The latter emphasized that previous studies did not successfully disentangle the association partly because of methodological discrepancies, but also because of poor quality of study designs: small sample sizes, important confounders not taken into account, or no time-varying associations tested. Overall, the main constraint was the cross-sectional design for most studies (108 cross-sectional versus 57 prospective cohorts). These issues may threaten the accuracy, reliability, and validity of the results, potentially leading to mixed evidence. Some studies reported that bullying victimization is associated with a reduced risk of engaging in harmful alcohol use (Moore et al., Reference Moore, Norman, Sly, Whitehouse, Zubrick and Scott2014; Nansel et al., Reference Nansel, Overpeck, Pilla, Ruan, Simons-Morton and Scheidt2001), others found no associations (Kelly et al., Reference Kelly, Newton, Stapinski, Slade, Barrett, Conrod and Teesson2015; Quinn et al., Reference Quinn, Fitzpatrick, Bussey, Hides and Chan2016; Tomczyk et al., Reference Tomczyk, Hanewinkel and Isensee2015), whereas others suggest that being bullied may result in an increased probability of later harmful alcohol use, even when important confounders such as use of drugs and peer drinking were controlled (Swahn et al., Reference Swahn, Topalli, Ali, Strasser, Ashby and Meyers2011; Tharp-Taylor et al., Reference Tharp-Taylor, Haviland and Amico2009). When pooled analysis was performed in the meta-analysis, a “possible causal” association between bullying victimization and alcohol use was found (Continuous Update Project Expert Report, 2018). The most recent studies investigating direct associations remain cross-sectional: being the target of bullying victimization, independent of adverse childhood experiences, was associated with increased odds of intoxication in the past 30 days compared to adolescents who did not experienced bullying victimization (Afifi et al., Reference Afifi, Taillieu, Salmon, Davila, Stewart-Tufescu, Fortier and MacMillan2020), and was associated with an increase in the adulthood prevalence of AUDs (Woo et al., Reference Woo, Chang, Hong, Lee, Hahm, Cho and Kim2019). Overall, these inconsistencies could be due to the cross-sectional nature of these studies and might also be partly due to confounding variables and individual differences that are not taken into account or investigated. Further longitudinal research that establishes temporal inference is needed to better explore the underlying time-varying mechanisms (when and how) bullying victimization is associated with alcohol use.

Testing hypotheses of temporal dynamics requires certain design qualities: 1. Temporal precedence (e.g., time-varying relationships are demonstrated); 2. Robust analytic methodology (e.g., structural equation modeling involving random intercepts to control for common vulnerability over time) 3. Mediation path (how long-term relationships are maintained) and 4. Specificity (under which conditions long-term relationships are explained). The key challenge is to find the right model that will disentangle this complex relationship. Thus, the current study aims to bring new evidence for time-varying associations by investigating overall, short-, and long-term associations between bullying victimization and alcohol use through mediation and moderation processes.

Psychopathology as a mediator

Integrating potential mediation effects is of particular interest for two reasons: (1) it provides important information for why and how relationships occur, (2) it allows to alleviate the underestimation of the effects sizes (Holbert & Stephenson, Reference Holbert and Stephenson2003). Broadly, it is the combination of direct and indirect effects that build the association between bullying victimization and alcohol use. Interestingly, Moore et al. (Reference Moore, Norman, Suetani, Thomas, Sly and Scott2017) concluded that there was “convincing evidence” for a temporal relationship between prior bullying victimization experiences and other psychopathological outcomes later, such as anxiety and depression, which are also known to further predict alcohol use (Hussong et al., Reference Hussong, Jones, Stein, Baucom and Boeding2011), indirectly implicating a mediation path from bullying victimization to alcohol use. The existence of this pathway might also explain the inconsistencies between studies: it is possible that effects on alcohol use will emerge later after the effects of the mediating variable have accumulated over time. As suggested by the self-medication hypotheses (the internalizing symptoms pathway), on which most studies are based, some adolescents might use alcohol as a maladaptive attempt to cope with or escape negative emotions elicited by bullying victimization (Khantzian, Reference Khantzian1997). Longitudinal studies consistently support this mediational pathway in adolescents (Earnshaw et al., Reference Earnshaw, Elliott, Reisner, Mrug, Windle, Emery and Schuster2017; Hong et al., Reference Hong, Davis, Sterzing, Yoon, Choi and Smith2014; Marschall-Lévesque et al., Reference Marschall-Lévesque, Castellanos-Ryan, Parent, Renaud, Vitaro, Boivin, Tremblay and Séguin2017; Meisel et al., Reference Meisel, Colder, Bowler and Hussong2018; Rowe et al., Reference Rowe, Zapolski, Hensel, Fisher and Barnes-Najor2019; Vannucci et al., Reference Vannucci, Fagle, Simpson and Ohannessian2020; Zapolski et al., Reference Zapolski, Rowe, Fisher, Hensel and Barnes-Najor2018). For instance, structural equation modelling findings demonstrated that more frequent experiences of bullying victimization in the 5th grade were associated with greater depressive symptoms in the 7th grade, which, in turn, were associated with a greater likelihood of alcohol use in the 10th grade (Earnshaw et al., Reference Earnshaw, Elliott, Reisner, Mrug, Windle, Emery and Schuster2017). In addition, Rowe et al. (Reference Rowe, Zapolski, Hensel, Fisher and Barnes-Najor2019) found a significant mediation path between 10th grade bullying victimization, 11th grade anxiety symptoms, and 12th grade alcohol use (similar results were found for the 9–11th grade path).

Although most studies are based on the self-medication hypothesis, there is evidence of a temporal association between bullying victimization and externalizing problems (Schoeler et al., Reference Schoeler, Duncan, Cecil and Ploubidis2018; Singham et al., Reference Singham, Viding, Schoeler, Arseneault, Ronald, Cecil and Pingault2017; van Lier et al., Reference van Lier, Vitaro, Barker, Brendgen, Tremblay and Boivin2012). Schoeler et al. (Reference Schoeler, Duncan, Cecil and Ploubidis2018) found evidence of “causal adverse effects” on both internalizing and externalizing domains after taking these shared genetic influences into account. Similarly, there is well-validated literature on the effect of externalizing problems on alcohol use (Colder et al., Reference Colder, Frndak, Lengua, Read, Hawk and Wieczorek2018; Farmer et al., Reference Farmer, Gau, Seeley, Kosty, Sher and Lewinsohn2016; Steele et al., Reference Steele, Forehand, Armistead and Brody1995). An alternative theory based on self-regulation hypotheses (the externalizing pathway), posits that the instability caused by bullying victimization may generate hostile social-cognitive biases (hostile automatic thoughts, dysfunctional inhibitory control) that reinforces the development of externalizing behaviors, which further engage peer-victimized adolescents more frequently in alcohol use than other adolescents (Dodge et al., Reference Dodge, Bates and Pettit1990). To our knowledge, the externalizing path between bullying victimization and alcohol use has only been tested in one prospective study. Contrary to expectations, there was a significant association between bullying victimization at age 14 and externalizing symptoms at age 18, but externalizing symptoms at age 18 did not significantly predict any further risk for alcohol misuse one year later (even after controlling for gender, age, family income and prior waves of alcohol use, externalizing, and internalizing symptoms). This finding suggests only concurrent relationships between externalizing and alcohol misuse symptoms (Meisel et al., Reference Meisel, Colder, Bowler and Hussong2018). When removing alcohol use at age 18 from the models, externalizing symptoms at age 18 significantly predict alcohol use at age 19. Thus, Meisel et al. (Reference Meisel, Colder, Bowler and Hussong2018) failed to reveal an externalizing mediation path because of strong contemporaneous correlations (strong within time correlation at age 18), and possibly because the onset of substance use at earlier stages of adolescence was not captured by the study. Further investigations are needed. Thus, the current study hypothesized that bullying victimization leads to alcohol use through two distinct time-varying mechanisms, the internalizing and externalizing pathways. Furthermore, the use of a more sensitive developmental design in the present study would help to disentangle temporal precedence in the onset of new victimization experiences and adolescent alcohol use.

Personality as a moderator

The mechanisms of action linking bullying victimization with alcohol use are certainly multifactorial and likely to differ across individual differences, reflecting pre-existing common vulnerabilities (Kavish et al., Reference Kavish, Connolly and Boutwell2019). The possibility that individual differences exist in the strength of the associations has not been systematically explored, yet, it might have important implications for intervention. Research focusing on factors that moderate consequences of bullying victimization is critical for understanding generalizability of a research finding (MacKinnon, Reference MacKinnon2011) and for supporting causal theories. It has been proposed that a number of potential moderators (e.g., gender, social support, attachment to school) could strengthen or weaken the association between bullying victimization and substance use (Hong et al., Reference Hong, Davis, Sterzing, Yoon, Choi and Smith2014). Gender is the most studied moderator in this field of research that has concluded gender-related biases towards internalizing versus externalizing behaviors following victimization experiences; however, many studies on bullying victimization have reported gender invariance (Forbes et al., Reference Forbes, Fitzpatrick, Magson and Rapee2019; Forbes et al., Reference Forbes, Magson and Rapee2020; Rosen et al., Reference Rosen, Beron and Underwood2013; Schaefer et al., Reference Schaefer, Moffitt, Arseneault, Danese, Fisher, Houts and Caspi2017). A growing body of research suggests that it may be less useful to take a gender-specific approach (Forbes et al., Reference Forbes, Magson and Rapee2020), and so, other individual characteristics should be more investigated.

Personality might be a better choice as moderator, which has some gender variance (Castonguay-Jolin et al., Reference Castonguay-Jolin, Perrier-Ménard, Castellanos-Ryan, Parent, Vitaro, Tremblay and Conrod2013; Woicik et al., Reference Woicik, Stewart, Pihl and Conrod2009), but might be more directly related to psychopathology outcomes of victimization than gender (Afzali, Sunderland, et al., Reference Afzali, Sunderland, Stewart, Masse, Seguin, Newton and Conrod2018; Calvete et al., Reference Calvete, Orue and Gamez-Guadix2016; Chinneck et al., Reference Chinneck, Thompson, Dobson, Stuart, Teehan and Stewart2018; Kaiser et al., Reference Kaiser, Davis, Milich and Smith2019; Kelly et al., Reference Kelly, Newton and Stapinski2018; Tani et al., Reference Tani, Greenman, Schneider and Fregoso1999). Personality has been independently implicated in risk for victimization (Bettencourt et al., Reference Bettencourt, Farrell, Liu and Sullivan2012; Hodges et al., Reference Hodges, Boivin, Vitaro and Bukowski1999; Juvonen & Graham, Reference Juvonen and Graham2014; Pellegrini, Reference Pellegrini1998), and risk for psychopathology (Prinstein et al., Reference Prinstein, Cheah and Guyer2005; Snyder et al., Reference Snyder, Brooker, Patrick, Snyder, Schrepferman and Stoolmiller2003; Van den Akker et al., Reference Van den Akker, Prinzie, Deković, De Haan, Asscher and Widiger2013). To clarify the question of personality profiles as a common vulnerability factor, the present study integrates two dimensions of personality profiles (externalizing personality profiles: impulsivity and sensation seeking; internalizing personality profiles: anxiety sensitivity and hopelessness) as moderators. These personality dimensions are high-risk predictors of substance use, and psychopathology : after controlling for gender, age, ethnicity, and baseline substance use or symptom measures, impulsivity showed a strong prospective association with substance use, conduct and hyperactivity problems; sensation seeking was associated with early onset and general drug use; hopelessness had a specific and strong association with depression symptoms, and anxiety sensitivity showed a strong prospective association with greater emotional symptoms (e.g., fear, worrying a lot) 18 months later (Castellanos-Ryan et al., Reference Castellanos-Ryan, O’Leary-Barrett, Sully and Conrod2013). Kelly et al. (Reference Kelly, Newton and Stapinski2018) reported that baseline hopelessness, impulsivity and low anxiety sensitivity in males predicted victimization 12-months later. Together, these studies suggest that these personality dimensions account for common vulnerability between victimization and psychopathology. Due to the complexity and computational burden of moderated mediation models, few studies have explored the moderating role of personality from a developmental perspective. Those with sufficient sample sizes and developmental data (Brendgen et al., Reference Brendgen, Wanner, Morin and Vitaro2005; Calvete et al., Reference Calvete, Orue and Gamez-Guadix2016; Gallardo-Pujol & Pereda, Reference Gallardo-Pujol and Pereda2013; Sugimura & Rudolph Reference Sugimura and Rudolph2012; Zhu et al., Reference Zhu, Yu, Zhang, Bao, Jiang, Chen and Zhen2016) have used multilevel analyses to reveal a weaker association between bullying victimization and social anxiety for adolescents with high extraversion, fewer depressive symptoms in adolescent victims with low extraversion (Calvete et al., Reference Calvete, Orue and Gamez-Guadix2016). Another study reported a larger effect of bullying victimization on behavioral problems among adolescents with high impulsivity compared to adolescents with low impulsivity (Zhu et al., Reference Zhu, Yu, Zhang, Bao, Jiang, Chen and Zhen2016). These findings remain limited by the lack of a unified framework, and the limited set of personality traits tested, thus limiting the ability to confirm specificity of effects and potential personality-specific pathways between bullying victimization and alcohol use. The current study aims to fill the third gap of the literature; hypothesising that bullying victimization leads to alcohol use under the conditional influence of personality profiles.

The current study

The current study provides a unique opportunity to apply a multilevel moderated mediation (conditional indirect effect) analysis to examining the specificity (personality), of multiple pathways (internalizing, externalizing paths) from bullying victimization to alcohol use. Despite the fact that moderated mediation models can extract more information than simplistic models, few studies ventured into these models, in part due to lack of large longitudinal dataset and because of the difficulty of specifying and interpreting these models (MacKinnon, Reference MacKinnon2011). Yet, moderated mediation analysis can help quantify more complicated hypotheses, force consideration of alternative interpretations of the results, and lead to better research designs and more information gleaned from the study (Preacher, Reference Preacher2015). Moreover, the design of the present study is rather unique, first, because of the large population-based sample of 3,800 adolescents followed over 5 years, and second, because of the advanced computational method, the Bayesian multilevel method, that can establish temporal precedence between variables. In the absence of the possibility to use experimental designs to establish time-varying associations of bullying victimization and alcohol use, developmental psychopathologists have now turned to the use of new computational methods in the form of multilevel models (MLMs), to establish temporal precedence in the relationship between two variables. Such models provide a rigorous test of predominance between two outcomes by quantifying the temporal association over multiple follow-up periods and by differentiating between-person, within-person, and lagged-within-person variance. This study investigated these effects while examining the “how” (mediation effect) and the “when” (moderation effect). In that respect, this is a rather markedly informative design enabling to test multiple concepts into one single model.

The current study examines broad levels of victimization, although many studies focus on specific form of victimization (i.e., physical, relational, and verbal) and its association with mental health. Results from a very well conducted study indicated that physical, verbal, and relational victimization had similar strength in associations across all levels of hierarchical model of psychopathology: specific diagnostics, internalizing versus externalizing dimensions, general factor of psychopathology (Forbes et al., Reference Forbes, Magson and Rapee2020). Therefore, broad level of victimization are chosen in this study. Similarly, the use of dimensional structure of psychopathology (internalizing and externalizing spectra) instead of discrete diagnostic categories (e.g., depression, anxiety, conduct, and hyperactivity problems) was carefully selected based on evidence of the well-validated internalizing-externalizing model (Conway et al., Reference Conway, Forbes, Forbush, Fried, Michael, Kotov and David2019; Forbes et al., Reference Forbes, Tackett, Markon and Krueger2016). When Forbes et al. (Reference Forbes, Magson and Rapee2020) investigated the robustness of associations between levels of hierarchical model, the strongest relationships were at the level of the transdiagnostic internalizing, externalizing, and general psychopathology factors compared to specific diagnostic. Thus, the internalizing and externalizing dimensions act as powerful pathway variables that might channel the effect of bullying victimization to alcohol use. In the present study, the internalizing factor represents the overlap between depressive symptoms and anxiety; and the externalizing factor represents the overlap between conduct, and hyperactivity problems. Finally, the present study integrates a large set of four personality traits (anxiety sensitivity, hopelessness, impulsivity, sensation seeking,) as moderators. These personality dimensions are high-risk predictors of substance use and specific psychopathology outcomes (Castellanos-Ryan et al., Reference Castellanos-Ryan, O’Leary-Barrett, Sully and Conrod2013). Thus, these personality traits are good candidates for conditional factors of the association between bullying victimization and alcohol use.

To conclude, the current study has three goals: (1) to investigate time-varying relationships between bullying victimization and alcohol use; (2) through internalizing and externalizing pathways; (3) conditional to the levels of personality profiles of adolescents over a 5-year period.

Method

Participants

Data from an ongoing population-based randomized controlled trial (Co-Venture) trial investigating the effectiveness of a 5-year personality-targeted drug and alcohol prevention program were used (O’Leary-Barrett et al., Reference O’Leary-Barrett, Mâsse, Pihl, Stewart, Séguin and Conrod2017). A large sample of adolescents (n = 3,800, 49.2% female, mean age = 12.8, SD = 0.4 years) was recruited from 31 schools in the Greater Montreal area. This sample of adolescents studied annually from 7th grade through 11th grade and was epidemiologically representative of each of its school districts. The sample of schools represents 15% of all schools across the greater Montreal area and each of their respective school districts in size and deprivation indexes within 1.5 standard deviations. Two exclusion criteria for schools were specified: the school had to agree to the study protocol and the school could not have more than 50% of its seventh-grade students having special educational needs. Most of the data collection took place in the spring each year. The sample was ethnically diverse, with 42% of the sample reporting Caucasian ethnic background.

Participants were invited to complete a confidential annual web-based survey during class time intended to assess clinical, cognitive and behavioral information. Confidentiality was accomplished by emphasizing that parents and teachers would not have access to the survey results and by automatically anonymizing the assessments. Among the 3,800 adolescents who were invited to complete the survey annually, 3,612 (94.4%) who passed the quality control of the different questionnaires and provided consistent minimal demographic information (sex, age, SES) were included in the analysis. Participants who provided odd response patterns (e.g., same response for every question) or unusually fast reaction time (i.e., having a mean RT of 200 ms throughout the task, 5.6%) were excluded from the study. Excluded participants were not significantly different from others in demographic information (sex, age, SES). Ethical approval was obtained from the ethical review board at the Sainte-Justine’s Hospital Ethics Committee in Montreal. All participants were included in the final study sample and analyses if 75% of their data across all items and annual survey waves were complete and reliable. Because more than 80% of the participants did not receive the targeted personality-based intervention, which was a non-intrusive 2 × 90 min s workshops, all participants were included in the final study sample. A sensitivity analysis will be conducted when approval to isolate data from non intervention schools will be granted. Attrition during the 5-year follow-up was 32% and was not significantly associated with participants’ characteristics.

Measures

Independent variables

Bullying victimization

Bullying victimization was measured by asking the participants to retrospectively report their experiences in the past 12 months using the validated and widely used Olweus Bully/Victim Questionnaire—BVQ (Lee & Cornell, Reference Lee and Cornell2009). This questionnaire includes 4 questions on victimization (e.g., “I was called names, was made fun of, or teased in a hurtful way”). Participants were asked to rate their response on a 5-point Likert scale (0 = never, 1 = only once or twice, 2 = two or three times a month, 3 = once a week, 5 = several times a week). Good internal reliability has been previously reported using the same 4 items for assessing exposure to bullying victimization in adolescence (Topper et al., Reference Topper, Castellanos-Ryan, Mackie and Conrod2011). In the present study, a good internal reliability was also shown for this measure (α = 0.85).

Personality risk profiles

Four personality traits were assessed using the Substance Use Risk Profile Scale (Woicik et al., Reference Woicik, Stewart, Pihl and Conrod2009). The SURPS is a 23-item questionnaire measuring personality risk for substance use and other behavioural problems according to four traits: anxiety–sensitivity (AS), described as a fear of anxiety-related physical sensations (e.g., “I get scared when I’m too nervous”), hopelessness (HOPE), a tendency towards low mood, worthlessness and negative beliefs about oneself, the world and the future (e.g., “I feel that I’m a failure”), sensation seeking (SS), defined by a low tolerance to boredom, a strong need for stimulation, and a willingness to take risks for the sake of having novel and varied experiences (e.g., “I enjoy new and exciting experiences even if they are unconventional”); and impulsivity (IMP), characterized by unplanned responses to internal or external stimulation or fast responses to given stimuli without deliberation and evaluation of consequences (e.g., “I often don’t think through before I speak”) (Newton et al., Reference Newton, Barrett, Castellanos-Ryan, Kelly, Champion, Stapinski and Teesson2016). This instrument has good concurrent, predictive and incremental validity with regards to differentiating individuals prone to reinforcement-specific patterns of substance use and has been shown to be sensitive and specific with respect to predicting future substance misuse and other mental health problems in adolescents (Castellanos-Ryan et al., Reference Castellanos-Ryan, O’Leary-Barrett, Sully and Conrod2013; Krank et al., Reference Krank, Stewart, O’Connor, Woicik, Wall and Conrod2011). Each personality trait was assessed using 5–7 items each rated on a 4-point scale (1 = strongly disagree, 2 = disagree, 3 = agree, 4 = strongly agree) (Castonguay-Jolin et al., Reference Castonguay-Jolin, Perrier-Ménard, Castellanos-Ryan, Parent, Vitaro, Tremblay and Conrod2013). Reliability alpha coefficients and score ranges for each subscale were as follows, anxiety sensitivity (range = 5–20, α = 0.76), hopelessness (range = 7–28, α = 0.85), impulsivity (rang e= 5–20, α = 0.79), and sensation seeking (range = 6–24, α = 0.73).

Mediators

Externalizing problems

Externalizing symptoms were measured by asking participants to rate the occurrence of conduct and hyperactivity problems within the last 12 months using the Strengths and Difficulties Questionnaire (Goodman, Reference Goodman2001). The SDQ is one of the most commonly used instruments for screening psychopathology in children and adolescents. SDQ has been widely validated in various community and clinical samples across different countries (Giannakopoulos et al., Reference Giannakopoulos, Dimitrakaki, Papadopoulou, Tzavara, Kolaitis, Ravens-Sieberer and Tountas2013). Each domain was assessed using five self-reported items rated on a 3-point scale, such as “I get very angry and often lose my temper” for conduct problems, and “I am easily distracted, I find it difficult to concentrate” for hyperactivity problems (0 = not true, 1 = somewhat true, 2 = certainly true). Reliability alpha coefficients for each subscale were as follows, conduct problems (range = 0–10, α = 0.62), hyperactivity (range = 0–10, α = 0.73). The externalizing problems variable was created using the sum of the total scores of conduct and hyperactivity problems.

Internalizing symptoms

Internalizing symptoms were measured by asking participants to indicate to what extend they experienced depressive and anxiety symptoms over the past 12 months using the Brief Symptoms Inventory. Subscales consists of 7 self-reported items of depressive symptoms (e.g., “Feeling no interest in things”) and five self-reported items of anxiety symptoms (e.g., “Spells of terror or panic”) rated on a 5-point scale (0 = not at all, 1 = a little bit, 2 = moderately, 3 = quite a bit, 4 = often). Reliability alpha coefficients for each subscale were as follows, depression (range = 0–28, α = 0.88), anxiety (range = 0–20, α = 0.87). The internalizing symptoms variable was created using the sum of the total scores of depressive and anxiety symptoms. Although the SDQ covers an emotional symptoms scale, it does not discriminate depressive, phobic, anxiety, and obsessive-compulsive disorders unlike the BSI, that is also more widely used to identify clinically relevant psychological symptoms (Goodman et al., Reference Goodman, Ford, Simmons, Gatward and Meltzer2000).

Dependent variable

Alcohol use

Alcohol use frequency was assessed using the validated ‘Detection of Alcohol and Drug Problems in Adolescents’ questionnaire (Landry et al., Reference Landry, Tremblay, Guyon, Bergeron and Brunelle2004). The DEP-ADO reliably identifies youth with alcohol and drug use disorders (onset, frequency, quantity and harm associated with alcohol and drug use) in the past 12 months. Scores are summed, and a substance use disorder is identified when total scores are greater than 20. The DEP-ADO has demonstrated good construct validity, internal consistency, test retest and intermodel execution reliability in Quebec youth (Landry et al., Reference Landry, Tremblay, Guyon, Bergeron and Brunelle2004). In the present study, a good reliability coefficient was also shown for this measure (α = 0.90). Self-report measures have been found to have excellent discrimination (Clark & Winters, Reference Clark and Winters2002) and predictive validity (White & Labouvie, Reference White and Labouvie1989) with regards to adolescent substance use and problems (Castellanos & Conrod, Reference Castellanos and Conrod2006; Conrod et al., Reference Conrod, Castellanos and Mackie2008; Conrod et al., Reference Conrod, Castellanos-Ryan and Strang2010; Conrod et al., Reference Conrod, Stewart, Comeau and Maclean2006). Participants rated their frequency of alcohol use on a 6-point scale (0 = Never, 1 = Occasionally, 2 = Monthly, 3 = 2–3 times per month, 4 = Weekly, 5 = Every day).

Covariates

Each model controlled for baseline socio-economic status (SES) and gender (0 = female, 1 = male). SES was assessed using the Family Affluence Scale for adolescents, items such as “How much pocket money do you get from your parent/guardian each week?” (0=0$; 1= 1–5$; 6=6–15$; 16=16–25$; 26=26–40$; 40=40$ or more) (Currie et al., 1997).

Analytical strategy

Data was analyzed using Mplus 8.4 statistical software. Bayesian multilevel modelling was conducted to assess conditional indirect effects (i.e., moderated mediation analysis) with bullying victimization as the independent variable, psychopathology as mediators, personality risk profiles as moderators, and alcohol use as the dependent variable (Figure 1). It has been demonstrated that performance of Bayesian methods yield higher power (e.g., unbiased estimates) compared to other traditional frequentist methods (e.g., maximum likelihood) to examine moderated mediation effects (Wang et al., Reference Wang, Preacher, Wang and Preacher2015). All measurement occasions were nested within students. Students were not nested in classrooms, neither schools because of the model capacity limitation: only one cluster is allowed in the Bayesian multilevel models.

Figure 1. Multilevel Bayesian model assessing the indirect association of bullying victimization and alcohol use through psychopathology and the potential mediating role of personality risk profiles.

Note. Time = the survey waves (YR = year). Curved arrows = between-person effects. Dashed arrows = within-person concurrent effects. Diagonal arrows = lagged-within-person effects. (Model 1a: X = bullying victimization, M = internalizing symptoms, Y= alcohol use; Model 1b: X = bullying victimization, M = externalizing problems, Y = alcohol use; Model 2a: X = bullying victimization high risk AS/HOPE, M = internalizing symptoms, Y = alcohol use; Model 2b: X = bullying victimization high risk IMP/SS, M = externalizing problems, Y = alcohol use)

Moderated mediation models were conducted. Each model distinguished the role of three aspects of bullying victimization: between-person effects (the effect of average bullying victimization over 5 years), within-person concurrent effects (change in level of bullying victimization within a given year compared to person’s mean bullying victimization within that same year) and lagged-within-person effects (level of bullying victimization the year before compared to person’s mean bullying victimization the following year). The time parameter (i.e., year of assessment) was coded from one to five.

The data analytical approach consisted of two steps. The first step estimated the indirect association between the predictor (i.e., bullying victimization) and the outcome variable (i.e., alcohol use) through each mediators (i.e., internalizing symptoms, externalizing problems) in two distinct models: model 1a assessed the indirect between-, within-, and lagged-within-person effects of bullying victimization on alcohol use through internalizing symptoms; model 1b assessed the indirect between-, within-, and lagged-within-person effects of bullying victimization on alcohol use through externalizing problems. The second step consisted of integrating all previously named parameters with the addition of the moderators (i.e., high AS/HOPE, high IMP/SS) in two distinct models: model 2a assessed the same parameters as in model 1a with the addition of high AS/HOPE as a moderator; model 2b assessed the same parameters as in model 1b with the addition of high IMP/SS as a moderator. Likewise, to assess the moderating role of low personality profiles, a new set of models were estimated following the same logic: model 3a assessed the same parameters as in model 1a with the addition of low AS/HOPE as a moderator; model 3b assessed the same parameters as in model 1b with the addition of low IMP/SS as a moderator. Model fit information were: model 1a (DIC= 276672.327), model 1b (DIC = 237639.330), model 2a (DIC= 392374.719), model 2b (DIC= 358525.646).

The “model constraint” command was used in Mplus to calculate the indirect effects based on the product of component path coefficients. Standard errors and 95% credibility intervals for indirect effects were calculated. To increase the clarity of our results the means, standard deviation, and correlations between the main variables is presented in Table 1. Analyses were conducted using the full-information maximum likelihood (FIML) estimation method to handle missing data. Estimation with FIML is superior to other procedures for handling missing data, and is less likely to produce biased estimates and standard errors (Schafer & Graham, Reference Schafer and Graham2002). Furthermore, there was only a small correlation between bullying victimization (each year) and the two baseline personality risk profiles (T1: β=.28 for high AS/HOPE; β=.10 for high IMP/SS; T2: β=.18 for high AS/HOPE; β=.11 for high IMP/SS; T3: β=.13 for high AS/HOPE; β=.08 for high IMP/SS; T4: β=.13 for high AS/HOPE; β=.07 for high IMP/SS; T5: β=.13 for high AS/HOPE; β=.11 for high IMP/SS), indicating that there are no collinearity issues in order to perform a moderation analysis.

Table 1. Means, Standard Deviations, and correlations among variables

Note. T1–T5 = Time 1–Time 5. M (SD) = Means (Standard Deviations). All correlations are significant at p < .05. No significance was found for 5 × 14, 5 × 18, 6 × 16, and 6 × 20.

Results

The indirect association of bullying victimization and alcohol use through internalizing symptoms (Model 1a)

The results (Table 2) indicated significant between-person mediation effect of bullying victimization (p < .0001) on alcohol use through internalizing symptoms over the five-year period, independent of within effects, SES, and gender: on average over the 5-year period, those prone to higher levels of bullying victimization are also prone to higher levels of alcohol and use, and this relationship was mediated by high overall levels of internalizing symptoms. Over and above the significant between effect, results also indicated a significant within-person mediation effect (p < .0001) and lagged-within-person mediation effect (p < .01): any further increases in exposure to bullying victimization in a given year were associated with increased risk of developing internalizing symptoms, and subsequently, alcohol use during the same year and one year later. At the between level, 6.7% of the variance in alcohol use was accounted for and 28.2% at the within level.

Table 2. Model 1a: Estimated parameters for multilevel models assessing internalizing symptoms as mediator of the temporal association between victimization and alcohol use

Note. Significant effects are marked in bold font (one-tailed p-value). ALC = alcohol use; INT = internalizing symptoms; SES = socio-economic status. Estimates were calculated using unstandardized beta.

The indirect association of bullying victimization and alcohol use through externalizing problems (Model 1b)

Regarding indirect associations of bullying victimization on alcohol use through externalizing problems, the results are presented in Table 3. There was a significant between-person mediation effect of bullying victimization (p < .0001), on alcohol use over and above within effects, SES, and gender. The results also indicated significant within-person mediation effect (p < .0001) and lagged-within-person mediation effect (p < .0001), while controlling for the between-person effect. At the between level, 12.6% of the variance in alcohol use was accounted for and 28.8% at the within level.

Table 3. Model 1b: Estimated parameters for multilevel models assessing externalizing problems as mediator of the temporal association between victimization and alcohol use

Note. Significant effects are marked in bold font. ALC = alcohol use; EXT = externalizing problems; SES = socio-economic status. Estimates were calculated using unstandardized beta.

The moderating effect of anxiety sensitivity and hopelessness between bullying victimization and alcohol use through internalizing symptoms (Models 2a, 3a)

Results are presented in Table 4, model 2a show a significant conditional indirect between-person effect (p < .0001) and within-person effect (p < .0001) of bullying victimization on alcohol use through internalizing symptoms for adolescents high in anxiety sensitivity or hopelessness. No conditional indirect lagged-within-person effect was found (p > .05). Conversely, the indirect between-person, within-person and lagged-within-person effects (p > .05) did not reach significance for those with low levels of these profiles. Thus, the indirect relationship between bullying victimization and alcohol through internalizing symptoms differs across levels of anxiety sensitivity and hopelessness. At the between level, 6.6% of the variance in alcohol use was accounted for and 27.9% at the within level (model 2a).

Table 4. Model 2a Estimated parameters for multilevel models assessing internalizing symptoms as mediator of the temporal association between victimization with high risk profile (anxiety sensitivity and hopelessness) and alcohol use

Note. Significant effects are marked in bold font (one-tailed p-value). ALC = alcohol use; INT = internalizing symptoms; SES = socio-economic status. Estimates were calculated using unstandardized beta.

The moderating effect of impulsivity and sensation seeking between bullying victimization and alcohol use through externalizing problems (Models 2b, 3b)

Results (Table 5) from the model 2b indicated that there was a conditional indirect effect of bullying victimization on alcohol use through externalizing problems: between-person, within-person, and lagged-within-person effects (p < .0001). Conversely, results from the model 3b showed no significant indirect between-person, within-, and lagged-within-person (p > .05) effects for adolescents low on these profiles. In other words, the effect of bullying victimization on alcohol use through externalizing problems is conditioned for adolescents with high level of impulsivity and sensation seeking. Thus, the indirect relationship between bullying victimization and alcohol through externalizing problems differs across levels of impulsivity and sensation seeking. At the between level, 13.6% of the variance in alcohol use was accounted for and 28.6% at the within level (model 2b).

Table 5. Model 2b Estimated parameters for multilevel models assessing externalizing symptoms as mediator of the temporal association between victimization with high risk profile (impulsivity and sensation seeking) and alcohol use

Note. Significant effects are marked in bold font (one-tailed p-value). ALC = alcohol use; EXT = externalizing problems; SES = socio-economic status. Estimates were calculated using unstandardized beta.

Discussion

By employing a rather advanced statistical modelling approach with a large population-based sample of 3,800 adolescents, the present study, investigated the mediating role of psychopathology in the time-varying associations between bullying victimization and alcohol use and the moderating role of personality risk profiles in this indirect association.

This study provides strong evidence for the existence of two indirect paths from bullying victimization to alcohol use through internalizing symptoms and externalizing problems. The two models (model 1a, 1b) both revealed between-person effects. That is, adolescents exposed to bullying victimization increase their general tendency toward alcohol use through the development of internalizing symptoms and externalizing problems, while controlling the effect of each variable across the 5-year period. Beyond this general tendency, within-, and lagged-within-person effects were observed, meaning that changes in level of exposure to bullying victimization within a given year predisposed adolescents to further alcohol use through the exacerbation of internalizing symptoms and externalizing problems in that same year (within-person effect) and one year later (lagged-within-person). Besides demonstrating strong evidence for temporal mediation effects, these latter results highlighted three important aspects of these mediations: they are general (between-), immediately experienced (concurrently, within-) and longer-lasting (lagged-). These results are in line with previous studies for the internalizing path (Earnshaw et al., Reference Earnshaw, Elliott, Reisner, Mrug, Windle, Emery and Schuster2017; Marschall-Lévesque et al., Reference Marschall-Lévesque, Castellanos-Ryan, Parent, Renaud, Vitaro, Boivin, Tremblay and Séguin2017; Rowe et al., Reference Rowe, Zapolski, Hensel, Fisher and Barnes-Najor2019; Vannucci et al., Reference Vannucci, Fagle, Simpson and Ohannessian2020; Zapolski et al., Reference Zapolski, Rowe, Fisher, Hensel and Barnes-Najor2018). However, results are conflicting with the results of the first study that investigated the externalizing path (Meisel et al., Reference Meisel, Colder, Bowler and Hussong2018), which did not find support for negative peer experiences operating through externalizing problems on alcohol use, although their initial assumption was in favor of the existence of the externalizing path. It is possible that adolescents exposed to bullying victimization learn to become more aggressive by being repeatedly reinforced for hitting or calling back onto their aggressors (Renouf et al., Reference Renouf, Brendgen, Séguin, Vitaro, Boivin, Dionne and Pérusse2010). Alternatively, repeated bullying victimization may generate a cognitive style that reinforces negative evaluations of the self and the future, and may lead to hypervigilance and a tendency to overestimate the level of threat (Espelage & Holt, Reference Espelage and Holt2001; Wang, Reference Wang2011). Future research should investigate differential cognitive styles for both internalizing and externalizing pathways.

This study then explored if personality risk profiles might explain differential reactivity to bullying victimization. When integrating high levels of anxiety sensitivity and hopelessness (model 2a), there was a between-, and a within-person conditional indirect effect of bullying victimization on alcohol use through internalizing symptoms. No lagged-within-person conditional indirect effect was found. This suggest that the strength of the indirect relation between bullying victimization and alcohol use depend on whether adolescents have high anxiety sensitivity and hopelessness. Similar conclusion can be drawn when investigating the conditional effect of high versus low levels of impulsivity and sensation seeking in the indirect association between bullying victimization and alcohol use through externalizing problems. High impulsivity and sensation seeking increased the indirect effect of bullying victimization at every level (between, within, and lagged); whereas no such effects were found with the low impulsivity and sensation seeking condition. The findings suggest that exposure to bullying victimization is more powerful in shaping externalizing problems towards alcohol use when adolescent individual characteristics are impulsivity and sensation seeking. This is in line with numerous studies demonstrating that personality factors are implicated in the vulnerability to adolescent alcohol use (Conrod et al., Reference Conrod, Castellanos and Mackie2008) and other psychopathological outcomes (Castellanos & Conrod, Reference Castellanos and Conrod2006; Krueger et al., Reference Krueger, Caspi, Moffitt, Silva and McGee1996). In this case, individual differences approach, such as focusing on personality-specific aspects, could be a major advantage when selecting, targeting, and assisting high-risk youth before they have initiated alcohol use. This approach will result in more sensitivity with respect to identifying current and future substance users. Overall, the current results suggest that bullying victimization may act as a stressor, generating specific manifestation of psychopathology sensitive to personality profiles, which makes bullying victimization pernicious and difficult to tackle.

The current study is not without limitations. First, self-reported measure of bullying victimization were collected in a classroom during school hours. Because of the sensitive nature of reporting bullying victimization surrounded by peers, it might have been underreported. To overcome this problem, trained staff supervised data collection, and therefore allowed a confidential context. Second, although important potential confounders were considered in the present study, it is possible that other factors, such as individual (e.g., puberty, gender) (Sontag et al., Reference Sontag, Graber and Clemans2011), familial (e.g., parenting) (Rudolph et al., Reference Rudolph, Monti, Modi, Sze and Troop-Gordon2020), or social (e.g., peer drinking) (Henneberger et al., Reference Henneberger, Mushonga and Preston2021) factors might affect the associations observed. For example, studies revealed that bullying victimization was indirectly associated with increased externalizing problems and alcohol use through deviant peer affiliation for both genders, and that impulsivity moderated theses associations (Jiang et al., Reference Jiang, Yu, Zhang, Bao and Zhu2016; Zhu et al., Reference Zhu, Yu, Zhang, Bao, Jiang, Chen and Zhen2016). Additional research is needed to shed light into these interactions, especially the role of gender. Third, although the intervention group accounted for a small portion of the sample, it is possible that the intervention had an effect on the outcome measures. Fourth, the present study investigated only the unidirectional path from bullying victimization to alcohol use; although, evidence for the reverse direction exists (Maniglio, Reference Maniglio2017). Future studies should address this issue with bidirectional effects, such as cross-lagged path model, but such designs should be sensitive to shorter time-interval when investigating lagged effects.

Despite these limitations, a major strength of the current study is the use of a large community sample size of 3,800 adolescents followed during 5 consecutive years, enhancing confidence in the generalizability of the results. In contrast to generalizability, another main strength is the unique methodological design that depicts an overall picture of how and when bullying victimization exposure tend to be the most harmful. The statistical model used was able to test specificity of effect by highlighting the importance of identifying high risk groups, to then enable to tailor intervention.

Intervention programs have usually limited resources to accomplish their goals. Intervention programs will cost less and provide greater benefits if the critical ingredients of interventions can be identified. Findings suggest that anti-bullying programs should adopt a different approach by removing ineffective components (Zych et al., Reference Zych, Farrington, Llorent and Ttofi2017) and adding targeted personality-based strategies to reduce the emergence of various psychopathological outcomes and prevent alcohol abuse later in life. Adolescents with different psychopathological patterns of victimization cannot be addressed with a uniform ‘one size fits all’ approach. Our previous research have brought new evidence in reducing victimization, internalizing symptoms, externalizing problems, and substance use through a selective intervention based on the four personality dimensions used in this study (Conrod et al., Reference Conrod, Topper, O’Leary-Barrett and Afzali2019; Kelly et al., Reference Kelly, Newton, Stapinski, Conrod, Barrett, Champion and Teesson2019; O’Leary-Barrett et al., Reference O’Leary-Barrett, Topper, Al-Khudhairy, Pihl, Castellanos-Ryan, Mackie and Conrod2013). For example, impulsivity-based intervention reduce conduct problems, and anxiety sensitivity-based intervention reduce anxiety symptoms (O’Leary-Barrett et al., Reference O’Leary-Barrett, Topper, Al-Khudhairy, Pihl, Castellanos-Ryan, Mackie and Conrod2013). There was higher levels of victimization among adolescents identified by personality risk, and the magnitude of decrease in victimization was higher among students who participated in the intervention (Conrod et al., Reference Conrod, Topper, O’Leary-Barrett and Afzali2019). Moreover, receiving the personality-based intervention was beneficial for adolescents who experienced bullying victimization regarding their alcohol-related harm compared to non-victimized adolescents (Edalati et al., Reference Edalati, Afzali, Castellanos-Ryan and Conrod2019).

The current study proposes a novel developmentally informed model to push research beyond a focus on simple cross-sectional associations and specific diagnostic pathology. The findings of the current study stress the need to regulate peer behavior. Individual’s own characteristics (personality profiles) and environmental factors (bullying victimization) appear to be a dangerous combination for overall, short-term, and long-term risks of developing psychopathology, and, further along engaging in alcohol use more severely than others who do not have these characteristics. In this study, new perspectives are provided by addressing the specifics how and for whom personality profiles can shape the immediate and long-term consequences of bullying victimization over the course of adolescence.

Acknowledgments

We would like to thank the participants of the Coventure project for making this study happen.

Funding statement

Funding for this study was provided by the Canadian Institutes of Health Research (grant FRN114887). PJC holds a Tier 1 Canada Research Chair, and a Research Chair in Social and Community Pediatrics, funded by Fondation Julien/Marcelle et Jean Coutu which supported FML’s studentship.

Conflicts of interest

None.

References

Afifi, T.O., Taillieu, T., Salmon, S., Davila, I.G., Stewart-Tufescu, A., Fortier, J., … MacMillan, H.L. (2020). Adverse childhood experiences (ACEs), peer victimization, and substance use among adolescents. Child Abuse & Neglect, 106, 104504. https://doi.org/10.1016/j.chiabu.2020.104504 CrossRefGoogle Scholar
Afzali, M., Sunderland, M., Stewart, S., Masse, B., Seguin, J., Newton, N., … Conrod, P. (2018). Machine-learning prediction of adolescent alcohol use : A cross-study, cross-cultural validation. Addiction, 114, 662671. https://doi.org/10.1111/add.14504 CrossRefGoogle Scholar
Bettencourt, A., Farrell, A., Liu, W., & Sullivan, T. (2012). Stability and change in patterns of peer victimization and aggression during adolescence. Journal of Clinical Child & Adolescent Psychology, 42, 429441. https://doi.org/10.1080/15374416.2012.738455 CrossRefGoogle Scholar
Brendgen, M., Wanner, B., Morin, A.J.S., & Vitaro, F. (2005). Relations with parents and with peers, temperament, and trajectories of depressed mood during early adolescence. Journal of Abnormal Child Psychology, 33, 579594. https://doi.org/10.1007/s10802-005-6739-2 CrossRefGoogle Scholar
Calvete, E., Orue, I., & Gamez-Guadix, M. (2016). Do extraversion and neuroticism moderate the association between bullying victimization and internalizing symptoms? A three-wave longitudinal study. Journal of School Psychology, 56, 111. https://doi.org/10.1016/j.jsp.2016.02.003 CrossRefGoogle Scholar
Castellanos, N., & Conrod, P. (2006). Brief interventions targeting personality risk factors for adolescent substance misuse reduce depression, panic and risk-taking behaviours. Journal of Mental Health, 15, 645658. https://doi.org/10.1080/09638230600998912 CrossRefGoogle Scholar
Castellanos-Ryan, N, O’Leary-Barrett, M., Sully, L., & Conrod, P. (2013). Sensitivity and specificity of a brief personality screening instrument in predicting future substance use, emotional, and behavioral problems: 18-month predictive validity of the substance use risk profile scale. Alcoholism: Clinical and Experimental Research, 37(SUPPL.1), 281290. https://doi.org/10.1111/j.1530-0277.2012.01931.x CrossRefGoogle Scholar
Castonguay-Jolin, L., Perrier-Ménard, E., Castellanos-Ryan, N., Parent, S., Vitaro, F., Tremblay, R.E., … Conrod, P.J. (2013). Validation de la traduction française de la SURPS pour une population d’adolescents québécois. TT – SURPS French version validation in a Quebec adolescent population. The Canadian Journal of Psychiatry/La Revue Canadienne de Psychiatrie, 58, 538545. https://doi.org/10.1177/070674371305800909.Validation CrossRefGoogle Scholar
Chinneck, A., Thompson, K., Dobson, K., Stuart, H., Teehan, M., & Stewart, S. (2018). Neurotic personality traits and risk for adverse alcohol outcomes: Chained mediation through emotional disorder symptoms and drinking to cope. Substance Use and Misuse, 53, 17301741. https://doi.org/10.1080/10826084.2018.1432647 CrossRefGoogle Scholar
Clark, D., & Winters, K. (2002). Measuring risks and outcomes in substance use disorders prevention research. Journal of Consulting and Clinical Psychology, 70, 12071223. https://doi.org/10.1037/0022-006X.70.6.1207 CrossRefGoogle Scholar
Colder, C.R., Frndak, S., Lengua, L.J., Read, J.P., Hawk, L.W. Jr., & Wieczorek, W.F. (2018). Internalizing and externalizing problem behavior : A test of a latent variable interaction predicting a two-part growth model of adolescent substance use. Journal of Abnormal Child Psycholy, 46, 319330. https://doi.org/10.1007/s10802-017-0277-6 CrossRefGoogle Scholar
Conrod, P, Castellanos, N., & Mackie, C. (2008). Personality-targeted interventions delay the growth of adolescent drinking and binge drinking. Journal of Child Psychology and Psychiatry, 49, 181190. https://doi.org/10.1111/j.1469-7610.2007.01826.x Google Scholar
Conrod, P, Castellanos-Ryan, N., & Strang, J. (2010). Brief, personality-targeted coping skills interventions and survival as a non-drug user over a 2-year period during adolescence. Archives of General Psychiatry, 67, 8593. https://doi.org/10.1001/archgenpsychiatry.2009.173 CrossRefGoogle Scholar
Conrod, P, Stewart, S., Comeau, N., & Maclean, A. (2006). Efficacy of cognitive-behavioral interventions targeting personality risk factors for youth alcohol misuse. Journal of Clinical Child and Adolescent Psychology, 35, 550563. https://doi.org/10.1207/s15374424jccp3504_6 CrossRefGoogle Scholar
Conrod, P., Topper, L., O’Leary-Barrett, M., & Afzali, M. (2019). Effects of school-based personality-targeted interventions on students’ self-report peer victimisation and perpetration of bullying behaviours. [Manuscript submitted for publication]. Department of Biomedical Sciences, University of Montreal.Google Scholar
Continuous Update Project Expert Report. (2018). Judging the Evidence. World Cancer Research Fund International. https://doi.org/10.1302/0301-620X.87B12.17247 Google Scholar
Conway, C., Forbes, M., Forbush, K., Fried, E., Michael, N., Kotov, R., … David, H. (2019). A hierarchical taxonomy of psychopathology can transform mental health research. Perspectives on Psychological Science, 14, 419436. https://doi.org/10.1177/1745691618810696.A CrossRefGoogle Scholar
Dodge, K., Bates, J., & Pettit, G. (1990). Mechanisms in the cycle of violence. Science, 250, 16781683. https://doi.org/10.1126/science.2270481 CrossRefGoogle Scholar
Earnshaw, V.A., Elliott, M.N., Reisner, S.L., Mrug, S., Windle, M., Emery, S.T., … Schuster, M.A. (2017). Peer victimization, depressive symptoms, and substance use: A longitudinal analysis. Pediatrics, 139, e20163426. https://doi.org/10.1542/peds.2016-3426 CrossRefGoogle Scholar
Edalati, H., Afzali, M., Castellanos-Ryan, N., & Conrod, P. (2019). The effect of contextual risk factors on the effectiveness of brief personality-targeted interventions for adolescent alcohol use and misuse: A cluster-randomized trial. Alcoholism: Clinical and Experimental Research, 43, 9971006. https://doi.org/10.1111/acer.14016 CrossRefGoogle Scholar
Espelage, D., & Holt, M. (2001). Bullying and victimization during early adolescence. Journal of Emotional Abuse, 2, 123142. https://doi.org/10.1300/J135v02n02 CrossRefGoogle Scholar
Evans-Lacko, S., Takizawa, R., Brimblecombe, N., King, D., Knapp, M., & Maughan, B. (2017). Childhood bullying victimization is associated with use of mental health services over five decades : A longitudinal nationally representative cohort study. Psychologicl Medicine, 127135. https://doi.org/10.1017/S0033291716001719 CrossRefGoogle Scholar
Farmer, R.F., Gau, J.M., Seeley, J.R., Kosty, D.B., Sher, K.J., & Lewinsohn, P.M. (2016). Internalizing and externalizing disorders as predictors of alcohol use disorder onset during three developmental periods. Drug and Alcohol Dependence, 164, 3846. https://doi.org/10.1016/j.drugalcdep.2016.04.021 CrossRefGoogle Scholar
Forbes, M., Fitzpatrick, S., Magson, N., & Rapee, R. (2019). Depression, anxiety, and peer victimization: Bidirectional relationships and associated outcomes transitioning from childhood to adolescence. Journal of Youth and Adolescence, 48, 692702. https://doi.org/10.1007/s10964-018-0922-6 CrossRefGoogle Scholar
Forbes, M., Magson, N., & Rapee, R. (2020). Evidence that different types of peer victimization have equivalent associations with transdiagnostic psychopathology in adolescence. Journal of Youth and Adolescence, 49, 590604. https://doi.org/10.1007/s10964-020-01202-4 CrossRefGoogle Scholar
Forbes, M., Tackett, J., Markon, K., & Krueger, R. (2016). Beyond comorbidity : Toward a dimensional and hierarchal approach to understanding psychopathology across the life span. Development and Psychopathology, 28, 971986. https://doi.org/10.1017/S0954579416000651 CrossRefGoogle Scholar
Gallardo-Pujol, D., & Pereda, N. (2013). Person–environment transactions: personality traits moderate and mediate the effects of child sexual victimization on psychopathology. Personality and Mental Health, 95, 8695. https://doi.org/10.1002/pmh Google Scholar
Giannakopoulos, G., Dimitrakaki, C., Papadopoulou, K., Tzavara, C., Kolaitis, G., Ravens-Sieberer, U., & Tountas, Y. (2013). Reliability and validity of the strengths and difficulties questionnaire in Greek adolescents and their parents. Health, 5, 17741783. https://doi.org/10.4236/health.2013.511239 CrossRefGoogle Scholar
Goodman, A. (2001). Psychometric properties of the strengths and difficulties questionnaire. Journal of the American Academy of Child & Adolescent Psychiatry, 40, 13371345. https://doi.org/10.1097/00004583-200111000-00015 CrossRefGoogle Scholar
Goodman, R., Ford, T., Simmons, H., Gatward, R., & Meltzer, H. (2000). Using the strengths and difficulties questionnaire (SDQ) to screen for children between 11 and 17 years old in a community sample. British Journal of Psychiatry, 177, 534539. Retrieved from https://pubmed.ncbi.nlm.nih.gov/11102329/ CrossRefGoogle Scholar
Hanna, E.Z., Yi, H.Y., Dufour, M.C., & Whitmore, C.C. (2001). The relationship of early-onset regular smoking to alcohol use, depression, illicit drug use, and other risky behaviors during early adolescence: Results from the youth supplement to the Third National Health and Nutrition Examination Survey. Journal of Substance Abuse, 13, 265282. https://doi.org/10.1016/S0899-3289(01)00077-3 CrossRefGoogle Scholar
Henneberger, A.K., Mushonga, D.R., & Preston, A.M. (2021). Peer influence and adolescent substance use: A systematic review of dynamic social network research. Adolescent Research Review, 6, 5773. https://doi.org/10.1007/s40894-019-00130-0 CrossRefGoogle Scholar
Hill, K.G., White, H.R., Chung, I., Hawkins, J.D., & Catalano, R.F. (2000). Early adult outcomes of adolescent Binge drinking: Person- and variable-centered analyses of Binge drinking trajectories. Alcoholism: Clinical and Experimental Research, 24, 892901.CrossRefGoogle Scholar
Hodges, E.V., Boivin, M., Vitaro, F., & Bukowski, W.M. (1999). The power of friendship: Protection against an escalating cycle of peer victimization. Developmental Psychology, 35, 94101. https://doi.org/10.1037/0012-1649.35.1.94 CrossRefGoogle Scholar
Holbert, L., & Stephenson, M. (2003). The importance of indirect effects in media effects research: Testing for mediation in structural equation modeling. Journal of Broadcasting & Electronic Media, 8151, 3741. https://doi.org/10.1207/s15506878jobem4704 Google Scholar
Hong, J.S., Davis, J.P., Sterzing, P.R., Yoon, J., Choi, S., & Smith, D.C. (2014). A conceptual framework for understanding the association between school bullying victimization and substance misuse. American Journal of Orthopsychiatry, 84, 696710. https://doi.org/10.1037/ort0000036 CrossRefGoogle Scholar
Hussong, A.M., Jones, D.J., Stein, G.L., Baucom, D.H., & Boeding, S. (2011). An internalizing pathway to alcohol use and disorder. Psychology of Addictive Behaviors, 25, 390404. https://doi.org/10.1037/a0024519 CrossRefGoogle Scholar
Jiang, Y., Yu, C., Zhang, W., Bao, Z., & Zhu, J. (2016). Peer victimization and substance use in early adolescence : Influences of deviant peer affiliation and parental knowledge. Journal of Child and Family Studies, 25, 21302140. https://doi.org/10.1007/s10826-016-0403-z CrossRefGoogle Scholar
Johnston, L.D., Miech, R.A., O’Malley, P.M., Bachman, J., Schulenberg, J., & Patrick, M. (2018). Monitoring the future national survey results on drug use, 1975–2018: Overview, key findings on adolescent drug use. National Survey Results on Drug Use, 1, 19752018.Google Scholar
Juvonen, J., & Graham, S. (2014). Bullying in schools : The power of bullies and the plight of victims. Annual Review of Psychology. https://doi.org/10.1146/annurev-psych-010213-115030 CrossRefGoogle Scholar
Kaiser, A., Davis, H., Milich, R., & Smith, G. (2019). Bidirectional relations of impulsive personality and alcohol use across three waves of data collection. Substance Use & Misuse, 53, 23862393. https://doi.org/10.1080/10826084.2018.1480036 CrossRefGoogle Scholar
Kavish, N., Connolly, E.J., & Boutwell, B.B. (2019). Genetic and environmental contributions to the association between violent victimization and major depressive disorder. Personality and Individual Differences, 140, 103110. https://doi.org/10.1016/j.paid.2018.05.034 CrossRefGoogle Scholar
Kelly, E, Newton, N., & Stapinski, L. (2018). Prospective associations between personality and bullying among Australian adolescents. Australian & New Zealand Journal of Psychiatry, 52, 173180. https://doi.org/10.1177/0004867417726583 CrossRefGoogle Scholar
Kelly, E.V., Newton, N.C., Stapinski, L.A., Conrod, P.J., Barrett, E.L., Champion, K.E., & Teesson, M. (2019). A novel approach to tackling bullying in schools: Personality-targeted intervention for adolescent victims and bullies in Australia. Journal of the American Academy of Child & Adolescent Psychiatry. https://doi.org/10.1016/j.jaac.2019.04.010 Google Scholar
Kelly, E.V., Newton, N.C., Stapinski, L.A., Slade, T., Barrett, E.L., Conrod, P.J., & Teesson, M. (2015). Concurrent and prospective associations between bullying victimization and substance use among Australian adolescents. Drug and Alcohol Dependence, 154, 6368. https://doi.org/10.1016/j.drugalcdep.2015.06.012 CrossRefGoogle Scholar
Khantzian, E.J. (1997). The self-medication hypothesis of substance use disorders: A reconsideration and recent applications. Harvard Review of Psychiatry, 4, 231244. https://doi.org/10.3109/10673229709030550 CrossRefGoogle Scholar
Krank, M., Stewart, S., O’Connor, R., Woicik, P., Wall, A., & Conrod, P. (2011). Structural, concurrent, and predictive validity of the substance use risk profile scale in early adolescence. Addictive Behaviors, 36, 3746. https://doi.org/10.1016/j.addbeh.2010.08.010 CrossRefGoogle Scholar
Krueger, R., Caspi, A., Moffitt, T., Silva, P., & McGee, R. (1996). Personality traits are differentially linked to mental disorders: A multitrait-multidiagnosis study of an adolescent birth cohort. Journal of Abnormal Psychology, 105, 299312. https://doi.org/10.1037/0021-843X.105.3.299 CrossRefGoogle Scholar
Landry, M., Tremblay, J., Guyon, L., Bergeron, J., & Brunelle, N. (2004). La Grille de dépistage de la consommation problématique d’alcool et de drogues chez les adolescents et les adolescentes (DEP-ADO) : développement et qualités psychométriques (Screening chart for problem consumption of alcohol and drugs among adolescents (DEP-aDO): Development and psychometric qualities). Drogues, Santé et Société, 3, 2037. https://doi.org/10.7202/010517ar CrossRefGoogle Scholar
Lee, T., & Cornell, D. (2009). Concurrent validity of the Olweus Bully/victim questionnaire. Journal of School Violence, 9, 5673. https://doi.org/10.1080/15388220903185613 CrossRefGoogle Scholar
MacKinnon, D.P. (2011). Integrating mediators and moderators in research design. Research on Social Work Practice, 21, 675681. https://doi.org/10.1177/1049731511414148 CrossRefGoogle Scholar
Maniglio, R. (2017). Bullying and other forms of peer victimization in adolescence and alcohol use. Trauma, Violence, & Abuse, 18, 457473. https://doi.org/10.1177/1524838016631127 CrossRefGoogle Scholar
Marschall-Lévesque, S., Castellanos-Ryan, N., Parent, S., Renaud, J., Vitaro, F., Boivin, M., Tremblay, R.E., & Séguin, J.R. (2017). Victimization, suicidal ideation, and alcohol use from age 13 to 15 years : Support for the self-medication model. Journal of Adolescent Health, 60, 380387. https://doi.org/10.1016/j.jadohealth.2016.09.019 CrossRefGoogle Scholar
Meisel, S.N., Colder, C.R., Bowler, J.C., & Hussong, A.M. (2018). A longitudinal examination of mediational pathways linking chronic victimization and exclusion to adolescent alcohol use Samuel. Developmental Psychology, 176, 139148. https://doi.org/10.1016/j.physbeh.2017.03.040 Google Scholar
Moore, S.E., Norman, R.E., Sly, P.D., Whitehouse, A.J.O., Zubrick, S.R., & Scott, J. (2014). Adolescent peer aggression and its association with mental health and substance use in an Australian cohort. Journal of Adolescence, 37, 1121. https://doi.org/10.1016/j.adolescence.2013.10.006 CrossRefGoogle Scholar
Moore, S.E., Norman, R.E., Suetani, S., Thomas, H.J., Sly, P.D., & Scott, J.G. (2017). Consequences of bullying victimization in childhood and adolescence: A systematic review and meta-analysis. World Journal of Psychiatry, 7, 6076. https://doi.org/10.5498/wjp.v7.i1.60 CrossRefGoogle Scholar
Nansel, T., Overpeck, M., Pilla, R., Ruan, W., Simons-Morton, B., & Scheidt, P. (2001). Bullying behaviors among US youth: Prevalence and association with psychosocial adjustment. Journal of the American Medical Association, 285, 20942100.CrossRefGoogle Scholar
Newton, N.C., Barrett, E.L., Castellanos-Ryan, N., Kelly, E., Champion, K.E., Stapinski, L., … Teesson, M. (2016). The validity of the Substance Use Risk Profile Scale (SURPS) among Australian adolescents. Addictive Behaviors, 53, 2330. https://doi.org/10.1016/j.addbeh.2015.09.015 CrossRefGoogle Scholar
O’Leary-Barrett, M., Mâsse, B., Pihl, R.O., Stewart, S.H., Séguin, J.R., & Conrod, P.J. (2017). A cluster-randomized controlled trial evaluating the effects of delaying onset of adolescent substance abuse on cognitive development and addiction following a selective, personality-targeted intervention programme: The Co-Venture trial. Addiction, 112, 18711881. https://doi.org/10.1111/add.13876 CrossRefGoogle Scholar
O’Leary-Barrett, M., Topper, L., Al-Khudhairy, N., Pihl, R.O., Castellanos-Ryan, N., Mackie, C.J., & Conrod, P.J. (2013). Two-year impact of personality-targeted, teacher-delivered interventions on youth internalizing and externalizing problems: A cluster-randomized trial. Journal of the American Academy of Child and Adolescent Psychiatry, 52, 911920. https://doi.org/10.1016/j.jaac.2013.05.020 CrossRefGoogle Scholar
Olweus, D. (1993). Bullying at School: What We Know and What We Can Do. Malden, MA: Blackwell Publishing. https://doi.org/10.1002/pits.10114 Google Scholar
Pellegrini, A.D. (1998). Bullies and victims in school : A review and call for research. Journal of Applied Developmental Psychology, 19, 165176.CrossRefGoogle Scholar
Preacher, K.J. (2015). Advances in mediation analysis: A survey and synthesis of new developments. Annual Review of Psychology, 66, 825852. https://doi.org/10.1146/annurev-psych-010814-015258 CrossRefGoogle Scholar
Prinstein, M.J., Cheah, C.S.J., & Guyer, A.E. (2005). Peer victimization, Cue interpretation, and internalizing symptoms: Preliminary concurrent and longitudinal findings for children and adolescents. Journal of Clinical Child and Adolescent Psychology, 34, 4961. https://doi.org/10.1207/s15374424jccp3401 CrossRefGoogle Scholar
Quinn, C.A., Fitzpatrick, S., Bussey, K., Hides, L., & Chan, G.C.K. (2016). Associations between the group processes of bullying and adolescent substance use. Addictive Behaviors, 62, 613. https://doi.org/10.1016/j.addbeh.2016.06.007 CrossRefGoogle Scholar
Renouf, A., Brendgen, M., Séguin, J., Vitaro, F., Boivin, M., Dionne, G., … Pérusse, D. (2010). Interactive links between theory of mind, peer victimization, and reactive and proactive aggression. Journal of Abnormal Child Psychology, 38, 11091123. https://doi.org/10.1007/s10802-010-9432-z CrossRefGoogle Scholar
Rosen, L., Beron, K., & Underwood, M. (2013). Assessing peer victimization across adolescence: Measurement invariance and developmental change. Psychological Assessment, 25, 111. https://doi.org/10.1037/a0028985 CrossRefGoogle Scholar
Rowe, A.T., Zapolski, T.C.B., Hensel, D.J., Fisher, S., & Barnes-Najor, J. (2019). Peer victimization, mood symptoms, and alcohol use: Examining effects among diverse high school youth. Journal of Youth and Adolescence, 48, 924934. https://doi.org/10.1007/s10964-018-0979-2 CrossRefGoogle Scholar
Rudolph, K.D., Monti, J.D., Modi, H., Sze, W.Y., & Troop-Gordon, W. (2020). Protecting youth against the adverse effects of peer victimization: Why do parents matter? Journal of Abnormal Child Psychology, 48, 163176. https://doi.org/10.1007/s10802-019-00576-9 CrossRefGoogle Scholar
Schaefer, J., Moffitt, T., Arseneault, L., Danese, A., Fisher, H., Houts, R., … Caspi, A. (2017). Adolescent victimization and early-adult psychopathology: Approaching causal inference using a longitudinal twin study to rule out noncausal explanations. Clinical Psychological Science, 120. https://doi.org/10.1177/2167702617741381 Google Scholar
Schafer, J.L., & Graham, J.W. (2002). Missing data: Our view of the state of the art. Psychological Methods, 7, 147177. https://doi.org/10.1037/1082-989X.7.2.147 CrossRefGoogle Scholar
Schoeler, T., Duncan, L., Cecil, C.M., & Ploubidis, G.B. (2018). Quasi-experimental evidence on short- and long-term consequences of bullying victimization : A meta-analysis. American Psychological Association, 144, 12291246.Google Scholar
Singham, T., Viding, E., Schoeler, T., Arseneault, L., Ronald, A., Cecil, C.M., … Pingault, J.-B. (2017). Concurrent and longitudinal contribution of exposure to bullying in childhood to mental health. JAMA Psychiatry, 74, 11121119. https://doi.org/10.1001/jamapsychiatry.2017.2678 CrossRefGoogle Scholar
Snyder, J., Brooker, M., Patrick, M.R., Snyder, A., Schrepferman, L., & Stoolmiller, M. (2003). Observed peer victimization during early elementary school: Continuity, growth, and relation to risk for child antisocial and depressive behavior. Child Development, 74, 18811898.CrossRefGoogle Scholar
Sontag, L.M., Graber, J.A., & Clemans, K.H. (2011). The role of peer stress and pubertal timing on symptoms of psychopathology during early adolescence. Journal of Youth and Adolescence, 40, 13711382. https://doi.org/10.1007/s10964-010-9620-8 CrossRefGoogle Scholar
Steele, R.G., Forehand, R., Armistead, L., & Brody, G. (1995). Predicting alcohol and drug use in early adulthood: The role of internalizing and externalizing behavior problems in early adolescence. American Journal of Orthopsychiatry, 65(3):380–388. https://doi.org/10.1037/h0079694 CrossRefGoogle Scholar
Sugimura, N., & Rudolph, K.D. (2012). Temperamental differences in children’s reactions to peer victimization. Journal of Clinical Child and Adolescent Psychology, 41, 314328. https://doi.org/10.1080/15374416.2012.656555 CrossRefGoogle Scholar
Swahn, M.H., Topalli, V., Ali, B., Strasser, S.M., Ashby, J.S., & Meyers, J. (2011). Pre-teen alcohol use as a risk factor for victimization and perpetration of bullying among middle and high school students in Georgia. Western Journal of Emergency Medicine, 12, 305309.Google Scholar
Tani, F., Greenman, P.S., Schneider, B.H., & Fregoso, M. (1999). Bullying and the big five: A study of childhood personality and participant roles in bullying incidents. School Psychology International, 24, 131146.CrossRefGoogle Scholar
Tharp-Taylor, S., Haviland, A., & Amico, E.J.D. (2009). Victimization from mental and physical bullying and substance use in early adolescence. Addictive Behaviors, 34, 561567. https://doi.org/10.1016/j.addbeh.2009.03.012 CrossRefGoogle Scholar
Tomczyk, S., Hanewinkel, R., & Isensee, B. (2015). Multiple substance use patterns in adolescents-A multilevel latent class analysis. Drug and Alcohol Dependence, 155, 208214. https://doi.org/10.1016/j.drugalcdep.2015.07.016 CrossRefGoogle Scholar
Topper, L.R., Castellanos-Ryan, N., Mackie, C., & Conrod, P.J. (2011). Adolescent bullying victimisation and alcohol-related problem behaviour mediated by coping drinking motives over a 12month period. Addictive Behaviors, 36, 613. https://doi.org/10.1016/j.addbeh.2010.08.016 CrossRefGoogle Scholar
Van den Akker, A.L., Prinzie, P., Deković, M., De Haan, A.D., Asscher, J.J., & Widiger, T. (2013). The development of personality extremity from childhood to adolescence: Relations to internalizing and externalizing problems. Journal of Personality and Social Psychology, 105, 10381048. https://doi.org/10.1037/a0034441 CrossRefGoogle Scholar
van Geel, M., Vedder, P., & Tanilon, J. (2014). Relationship between peer victimization, cyberbullying, and suicide in children and adolescents. JAMA Pediatrics, 168, 435. https://doi.org/10.1001/jamapediatrics.2013.4143 CrossRefGoogle Scholar
van Lier, P.A.C., Vitaro, F., Barker, E.D., Brendgen, M., Tremblay, R.E., & Boivin, M. (2012). Peer victimization, poor academic achievement, and the link between childhood externalizing and internalizing problems. Child Development, 83, 17751788. https://doi.org/10.1111/j.1467-8624.2012.01802.x CrossRefGoogle Scholar
Vannucci, A., Fagle, T.R., Simpson, E.G., & Ohannessian, C.M.C. (2020). Perceived family and friend support moderate pathways from peer victimization to substance use in early-adolescent girls and boys: A moderated-mediation analysis. Journal of Early Adolescence. https://doi.org/10.1177/0272431620931187 Google Scholar
Wang, C. (2011). A longitudinal investigation of peer victimization, self-esteem, depression, and anxiety among adolescents: A test of cognitive diathesis-stress theory. Public Access Theses and Dissertations from the College of Education and Human Sciences, 110.Google Scholar
Wang, L.P., Preacher, K.J., Wang, L.P., & Preacher, K.J. (2015). Moderated mediation Analysis using Bayesian methods moderated mediation analysis using Bayesian methods. Structural Equation Modeling: A Multidisciplinary Journal, 22, 249263. https://doi.org/10.1080/10705511.2014.935256 CrossRefGoogle Scholar
White, H., & Labouvie, E. (1989). Towards the assessment of adolescent problem drinking. Journal of Studies on Alcohol, 50, 3037.CrossRefGoogle Scholar
Woicik, P.A., Stewart, S.H., Pihl, R.O., & Conrod, P.J. (2009). The substance use risk profile scale: A scale measuring traits linked to reinforcement-specific substance use profiles. Addictive Behaviors, 34, 10421055. https://doi.org/10.1016/j.addbeh.2009.07.001 CrossRefGoogle Scholar
Woo, J., Chang, S.M., Hong, J.P., Lee, D.W., Hahm, B.J., Cho, S.J., … Kim, B.S. (2019). The association of childhood experience of peer bullying with DSM-IV psychiatric disorders and suicidality in adults: Results from a nationwide survey in Korea. Journal of Korean Medical Science, 34, 112. https://doi.org/10.3346/jkms.2019.34.e295 CrossRefGoogle Scholar
Zapolski, T.C.B., Rowe, A.T., Fisher, S., Hensel, D.J., & Barnes-Najor, J. (2018). Peer victimization and substance use : Understanding the indirect effect of depressive symptomatology across gender. Addictive Behaviors, 84, 160166. https://doi.org/10.1016/j.addbeh.2018.04.010 CrossRefGoogle Scholar
Zhu, J., Yu, C., Zhang, W., Bao, Z., Jiang, Y., Chen, Y., & Zhen, S. (2016). Peer victimization, deviant peer affiliation and impulsivity: Predicting adolescent problem behaviors. Child Abuse & Neglect, 58, 3950. https://doi.org/10.1016/j.chiabu.2016.06.008 CrossRefGoogle Scholar
Zych, I., Farrington, D.P., Llorent, V.J., & Ttofi, M.M. (2017). Protecting Children Against Bullying and Its Consequences. Fort Lauderdale: SpringerBriefs in Psychology.CrossRefGoogle Scholar
Figure 0

Figure 1. Multilevel Bayesian model assessing the indirect association of bullying victimization and alcohol use through psychopathology and the potential mediating role of personality risk profiles.Note. Time = the survey waves (YR = year). Curved arrows = between-person effects. Dashed arrows = within-person concurrent effects. Diagonal arrows = lagged-within-person effects. (Model 1a: X = bullying victimization, M = internalizing symptoms, Y= alcohol use; Model 1b: X = bullying victimization, M = externalizing problems, Y = alcohol use; Model 2a: X = bullying victimization high risk AS/HOPE, M = internalizing symptoms, Y = alcohol use; Model 2b: X = bullying victimization high risk IMP/SS, M = externalizing problems, Y = alcohol use)

Figure 1

Table 1. Means, Standard Deviations, and correlations among variables

Figure 2

Table 2. Model 1a: Estimated parameters for multilevel models assessing internalizing symptoms as mediator of the temporal association between victimization and alcohol use

Figure 3

Table 3. Model 1b: Estimated parameters for multilevel models assessing externalizing problems as mediator of the temporal association between victimization and alcohol use

Figure 4

Table 4. Model 2a Estimated parameters for multilevel models assessing internalizing symptoms as mediator of the temporal association between victimization with high risk profile (anxiety sensitivity and hopelessness) and alcohol use

Figure 5

Table 5. Model 2b Estimated parameters for multilevel models assessing externalizing symptoms as mediator of the temporal association between victimization with high risk profile (impulsivity and sensation seeking) and alcohol use