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  • 1 Middlebury College, USA
  • | 2 Yale School of Medicine, USA
  • | 3 Retired, Guilford, CT, USA
  • | 4 Problem Gambling Services, USA
  • | 5 The Connecticut Council on Problem Gambling, USA
  • | 6 The Connecticut Mental Health Center, USA
  • | 7 Yale School of Medicine, USA
Open access

Background and aims

A recent call to action highlighted the need to understand the relationship between problem gambling, violence, and health/functioning. As weapon-carrying and gambling behaviors are prevalent in adolescents, this study systematically examined relationships between weapon-carrying status and measures of problem gambling severity and gambling perceptions and attitudes, as well as how weapon-carrying status moderated relationships between problem gambling severity and measures of health/functioning and gambling behavior.

Methods

Participants were 2,301 Connecticut high-school adolescents. χ2 and logistic regression models were conducted.

Results

Weapon-carriers reported greater problem gambling severity, more permissive gambling perceptions, greater parental approval of gambling, and more family gambling concerns, compared to non-weapon-carriers. At-risk/problem gambling was more strongly associated with family, peers, and adult gambling partners among non-weapon-carriers (vs. weapon-carriers) and with machine gambling among weapon-carriers (vs. non-weapon-carriers).

Discussion and conclusions

Greater problem gambling severity and more permissive gambling perceptions and perceived parental approval of gambling in weapon-carrying adolescents suggest that parent–child relationships are important to be considered in prevention efforts. The moderated relationship by weapon-carrying status between problem gambling severity and gambling partners suggests a problem gambling risk group that may be less linked to gambling with traditional social support groups, and this group may benefit from targeted interventions.

Abstract

Background and aims

A recent call to action highlighted the need to understand the relationship between problem gambling, violence, and health/functioning. As weapon-carrying and gambling behaviors are prevalent in adolescents, this study systematically examined relationships between weapon-carrying status and measures of problem gambling severity and gambling perceptions and attitudes, as well as how weapon-carrying status moderated relationships between problem gambling severity and measures of health/functioning and gambling behavior.

Methods

Participants were 2,301 Connecticut high-school adolescents. χ2 and logistic regression models were conducted.

Results

Weapon-carriers reported greater problem gambling severity, more permissive gambling perceptions, greater parental approval of gambling, and more family gambling concerns, compared to non-weapon-carriers. At-risk/problem gambling was more strongly associated with family, peers, and adult gambling partners among non-weapon-carriers (vs. weapon-carriers) and with machine gambling among weapon-carriers (vs. non-weapon-carriers).

Discussion and conclusions

Greater problem gambling severity and more permissive gambling perceptions and perceived parental approval of gambling in weapon-carrying adolescents suggest that parent–child relationships are important to be considered in prevention efforts. The moderated relationship by weapon-carrying status between problem gambling severity and gambling partners suggests a problem gambling risk group that may be less linked to gambling with traditional social support groups, and this group may benefit from targeted interventions.

Introduction

Weapon-carrying in adolescents, including possession of firearms, knives, or clubs, is a common type of youth violence that is a persistent concern in the United States and other countries. In a cross-national study, 10%–12% of boys and 2%–5% of girls reported having carried a weapon (Pickett et al., 2005). In the United States, 15.7% of adolescent students carried a weapon and 3.8% carried a weapon on school grounds in 2017 (Centers for Disease Control and Prevention, 2019). Weapon-carrying has been associated with heightened risk of mental and physical health problems, including depression, suicidal ideation, disordered eating, sexual victimization, and severe injuries requiring hospitalization (Muula, Rudatsikira, & Siziya, 2008; Pickett et al., 2005; Ruggles & Rajan, 2014). In addition, those who used weapons in fights were more likely to be regular smokers and sensation seekers, practice unsafe sex, and have poor family relationships (Thurnherr, Michaud, Berchtold, Akré, & Suris, 2009).

Inasmuch as an estimated 60%–70% of North American youth have reported gambling and up to 10% of adolescents and young adults in the US have reported gambling problems in the past year (Barnes, Welte, Hoffman, & Tidwell, 2009; Volberg, Gupta, Griffiths, Olason, & Delfabbro, 2010), growing evidence point to a consistent relationship between weapon-carrying and problem gambling. Findings from the Centers for Disease Control and Prevention Youth Risk Behavioral Survey have shown that violence including carrying a weapon and physical fighting was associated with greater likelihoods of past-year gambling and gambling problems, and remained significant even after controlling other risky behaviors of substance use and sexual activity (Proimos, DuRant, Pierce, & Goodman, 1998). Furthermore, adolescents who carried a weapon were nearly three times more likely to have gambled in the past year (Goldstein, Walton, Cunningham, Resko, & Duan, 2009). Similarly, individuals with problem gambling have greater odds of weapon-carrying, firearms carrying, as well as physical violence (Cook et al., 2015; Potenza et al., 2011; Slavin et al., 2013).

Both adolescent gambling and weapon-carrying are problem behaviors that share associations with negative health/functioning, including substance use, poor academic performance, depression, and delinquency (Cook et al., 2015; Mishra, Lalumière, Morgan, & Williams, 2011; Yip et al., 2011). A problem behavior theory proposes that youth risky behaviors associated with weapons-carrying and gambling commonly co-occur from person–environment interactions and both may be contributing factors to a larger complex syndrome of “multiproblem” behaviors that portend serious health concerns (Donovan & Jessor, 1985; Jessor & Jessor, 1977; Kryszajtys et al., 2018; Pickett et al., 2002). Consistent with problem behavior theory, problem gambling and weapon-carrying were hypothesized to be linked through shared vulnerabilities, particularly in impulse control, family/peer relationships, and their interactions with youth environments (Mishra et al., 2011; Vitaro, Brendgen, Ladouceur, & Tremblay, 2001).

Together, findings suggest that problem gambling and weapon-carrying impact subsequent health and function, and are strongly associated in adolescents. However, differences in complex health/functioning characteristics and gambling behavior correlates of problem gambling between adolescent students of different weapon-carrying status remain poorly understood. In addition, although both problem gambling and weapon-carrying are related to risk behaviors, few studies have directly examined interactions between problem gambling and weapon-carrying status on health/functioning (Kryszajtys et al., 2018). Understanding these relationships is critical to advancing prevention efforts focused on both gambling and weapon-carrying behaviors among youth.

Hence, this study examined the relationship between problem gambling severity and health/functioning, and gambling behaviors in adolescents stratified by weapon-carrying status. We hypothesized that weapon-carrying would be associated with more severe problem gambling; adolescents with weapon-carrying would have more permissive gambling perceptions and view problem gambling preventions as less important; and the relationship between problem gambling severity and health/functioning and gambling characteristics would differ between weapon-carrying and non-weapon-carrying adolescents.

Participants in this study have reported a variety of risky behaviors, and include adolescents who may carry a weapon for self-defense, to perpetrate violence, or both. Previous findings have shown that adolescent victimization and perpetration of violence and bullying are associated with weapon-carrying (Durant, Getts, Cadenhead, & Woods, 1995; Erickson, Butters, Cousineau, Harrison, & Korf, 2006; van Geel, Vedder, & Tanilon, 2014). Both bullying victim and perpetrator status were shown to mediate obesity and weapon-carrying relationships, suggesting that significant health problems may occur in adolescents who attribute weapon-carrying to either violence perpetration or victimization (Kukaswadia, Craig, Janssen, & Pickett, 2012). Adolescent perpetrators of violence are often also bullying victims and carry a weapon consequent to having experienced violence (Erickson et al., 2006; Leary, Kowalski, Smith, & Phillips, 2003). Indeed, recent evidence showed that adolescents who perpetrated and were victims of bullying through electronic venues (i.e., cyberbullying) were 2.65 times more likely to prospectively report weapon-carrying 1 year later (Lu, Avellaneda, Torres, Rothman, & Temple, 2019). As it is difficult to determine motivations for weapon-carrying, participants who endorsed weapon-carrying in this study were considered as a whole, as there was no indication for the rationale of weapon-carrying.

Methods

Recruitment and survey characteristics

Recruitment, consenting procedures, and sample characteristics have been reported previously (Potenza et al., 2011; Schepis et al., 2008; Zhai et al., 2017). Briefly, invitations were extended through mailing 122 letters and follow-up calls to principals of 4-year and non-vocational or special-education high schools in Connecticut, USA. Seventy-eight schools did not respond and 13 declined. Additional targeted recruitment, conducted to ensure representation of all four geographical quadrants of Connecticut, and schools from the three tiers of the state’s family-socioeconomic-status-related district reference groups, yielded 10 schools that participated in the survey. Adolescents were surveyed over one academic year. For each school, the survey was administered on a single day by the research team. There was no monetary compensation and refusal rate was <1%.

Descriptions of the variables and classification of responses were previously presented (Potenza et al., 2011; Schepis et al., 2008; Yip et al., 2011). The survey contained 154 questions assessing demographic characteristics, health/functioning measures, gambling (defined as “any game you bet on for money or anything else of value”), and items derived from established measures (e.g., Massachusetts Gambling Screen by Shaffer, Labrie, Scanlan, & Cummings, 1994). For this study, 2,301 adolescents completed the weapon-carrying measure and all 12 questions corresponding to inclusion criteria for problem/pathological gambling.

Measures

Demographic characteristics

As reported previously (Schepis et al., 2008; Yip et al., 2011), sample demographics were consistent with findings reported in the 2000 Census of Connecticut residents aged 14–18 years. Demographic variables controlled for herein regarding adolescent problem gambling severity included gender, race/ethnicity, grade in school, and family structure (e.g., living with one parent).

Problem gambling severity

Problem gambling severity was assessed using the Massachusetts Gambling Screen (Shaffer et al., 1994), a validated self-report assessment tool based on DSM-IV criteria for pathological gambling (American Psychiatric Association, 2000; Weinstock, Whelan, & Meyers, 2004). The Massachusetts Gambling Screen (MAGS) was developed to yield an index for pathological gambling. Subscales had adequate reliability (Cronbach’s α = .83–.87). For predictive validity, the instrument was able to classify 96% of students as having pathological or non-pathological gambling (Shaffer et al., 1994).

Weapon-carrying

Weapon-carrying status was assessed using the question “During the past 30 days, on how many days did you carry a weapon, such as a gun, knife, or club?” This item is consistent with previous studies that similarly assessed weapon-carrying regardless of weapon type (Durant et al., 1995), or combined different weapon types into one factor (Kukaswadia et al., 2012).

Gambling perceptions

Adolescent perceptions of gambling and the importance of preventing problem gambling were assessed as described previously (Slavin et al., 2013; Yip et al., 2011). Participants indicated the importance (important/not important) on 15 items regarding gambling prevention approaches. Examples include “Checking identification for purchasing lottery tickets,” “Hanging out with friends who do not gamble,” and “Participating in activities that are fun and free of gambling.” In addition, participants reported on perceived parental perceptions toward gambling (disapprove, approve, or neither) with the item “How do you think your parents would feel about you gambling, even once or twice, over the next 12 months?” Adolescents’ perceptions of having family gambling problems (yes/no) were assessed with the question, “Has the gambling of a close family member caused you worry or concern?”

Health/functioning

As previously described (Slavin et al., 2013; Yip et al., 2011), health/functioning measures assessed the following domains: grade average, engagement in extracurricular activity (yes/no), lifetime regular tobacco smoking (never, occasionally, and regularly), lifetime marijuana use (yes/no), lifetime other drug use (yes/no), lifetime (yes/no) and past-30-days alcohol use [never, regular (1–5 days), light (6–9 days), moderate (10–19 days), and heavy (20–30 days)], and past-year sadness or hopelessness for ≥2 consecutive weeks (yes/no). Height and weight were assessed to calculate body mass index (BMI). BMIs were categorized as underweight (≤18.5), normal weight (18.6–24.9), overweight (25–29.9), and obese (≥30).

Gambling characteristics

Participants with past-year gambling responded on the presence (yes/no) of different gambling characteristics including: gambling location (online, school grounds, and casino), gambling triggers (pressure and anxiety), gambling reasons (excitement, financial, escape, and social), gambling partners (family, friends, other adults, strangers, and alone), time spent gambling per week (≤1 and ≥2 hr), and gambling age of onset (≤8, 9–11, 12–14, and ≥15 years old). Gambling types were classified into strategic gambling (i.e., so-called “games of skill” involving chance), non-strategic gambling (i.e., “games of chance” not involving skill), and machine gambling as previously defined (Yip et al., 2011). Machine gambling was determined by endorsement of having wagered on slot machines, poker machines, or other gambling machines.

Procedure

Problem gambling severity groups

Participants were stratified into three problem gambling severity groups based on MAGS responses. Adolescents with no past-year gambling were classified as non-gambling (NG). As in prior studies (Potenza et al., 2011; Slavin et al., 2013; Yip et al., 2011; Zhai et al., 2017) and US national epidemiological samples (Desai & Potenza, 2008; Pilver, Libby, Hoff, & Potenza, 2013a, 2013b), adolescents with past-year gambling but no diagnostic criteria were classified as low-risk gambling (LRG). Adolescents who endorsed one or more criteria were classified as at-risk/problem gambling (ARPG). Among the 2,301 adolescents, designations included 406 (17.6%) with NG, 1,254 (54.5%) with LRG, and 641 (27.9%) with ARPG. For follow-up analyses, adolescents with gambling were also stratified based on the number of endorsed pathological-gambling criteria (Pilver et al., 2013b). Of the 1,895 adolescents who gambled, designations included 1,254 with 0 inclusionary criteria (66.2%), 405 with 1–2 criteria (21.4%), 115 with 3–4 criteria (6.1%), and 121 with ≥5 criteria (6.4%).

Weapon-carrying groups

Adolescent were also stratified into two weapon-carrying groups. Those who gave a response of 0 days in which they carried weapons were designated as non-weapon-carrying, and responses greater than 0 were designated as weapon-carrying. Among the 2,301 adolescents in this study, 599 (26%) reported weapon-carrying.

Statistical analyses

As described previously (Slavin et al., 2013; Yip et al., 2011), data were double-entered and random spot-checks of completed surveys were performed to ensure accuracy. Statistical analyses were conducted using SPSS 24 (Armonk, NY, USA). Pearson’s χ2 analyses (two-tailed) compared demographic characteristics and gambling perceptions stratified by weapon-carrying status. A Bonferroni correction for multiple χ2 comparisons was applied such that p values of p ≤ .0025 were considered significant. Logistic regression models were constructed for binary outcomes and multinomial logistic regression models for categorical outcomes, stratified by weapon-carrying status, to calculate odds ratios (ORs) and 95% confidence intervals for the association between problem gambling severity and dependent variables. To determine the interaction between weapon-carrying status and problem gambling severity on dependent variables, main effects of weapon-carrying status and problem gambling severity, and the interaction term (weapon-carrying by problem gambling severity), were included in the models. All interaction models were adjusted for gender, grade level, race, and family structure and significance was set at p ≤ .05.

Ethics

Among schools that were interested in participating, permission was obtained from school boards and/or superintendents as necessary. The institutional review board at Yale University and all data collection sites approved the passive parental consent and student assent procedures. Letters were sent to parents to provide information about the study and instructed them to contact the school should they deny the permission. Students were given the opportunity to decline participation. All procedures performed in human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Results

Demographic characteristics

Demographic data are shown in Table 1. Among weapon-carriers, 78% were male and 21.7% were female, and 16.3% of weapon-carrying adolescents were aged ≤14 years, 68.4% were between 15 and 17 years, and 15.3% were ≥18 years. Among these students, 33.6%, 24.5%, 28.4%, and 13.4% attended 9th, 10th, 11th, and 12th grades, respectively. Furthermore, 69% of weapon-carrying adolescents identified as Caucasian, 14.1% as African American, 5.9% as Asian American, 20.6% as Hispanic, and 19.5% as “other race.” Weapon-carrying status was associated with problem gambling severity. Weapon-carriers reported ARPG (46.9%) more frequently relative to non-weapon-carriers (21.2%). Among adolescents who gambled, weapon-carrying was associated with problem gambling severity levels (p < .001). Weapon-carriers reported 1–2 (26.3%), 3–4 (9.4%), and ≥5 (15.0%) criteria more frequently relative to non-weapon-carriers (19.3%, 4.7%, and 2.8%, respectively). Based on the sample characteristics, the study may not be sufficiently powered to reliably examine further interactions by multiple demographic variables (e.g., gender) between different weapon-carrying and problem gambling severity groups.

Table 1.

Sociodemographic characteristics stratified by weapon-carrying status

Non-weapon-carrying (N = 1,702)Weapon-carrying (N = 599)
VariableN%N%χ2p
Gender162.06<.0001
 Male8104845978
 Female8775212721.7
Race/ethnicity
 Caucasian3.97.046
  No45426.718431
  Yes1,24573.341069
 African American7.64.006
  No1,5299051085.9
  Yes170108414.1
 Asian1.44.230
  No1,62095.455994.1
  Yes794.6355.9
 Hispanic14.49<.0001
  No1,39886.145179.4
  Yes22513.911720.6
 Other5.39.020
  No1,43784.647880.5
  Yes26215.411619.5
Grade12.48.006
 9th48228.420033.6
 10th44025.914624.5
 11th45426.716928.4
 12th322198013.4
Age (years).03.990
 <1421316.47716.3
 15–1788868.632268.4
 >1819415.07215.3
Family structure33.44<.0001
 One parent35020.917029
 Two parents1,23573.635961.3
 Other935.5579.7
Problem gambling severity165.61<.0001
 Non-gambling36221.3447.3
 Low-risk gambling98057.627445.7
 At-risk/problem gambling36021.228146.9
Pathological gambling criteria146.80<.001
 None98073.127449.4
 1–2 symptoms25919.314626.3
 3–4 symptoms634.7529.4
 ≥5 symptoms382.88315.0

Note. Total sample size (N = 2,301). Percentages presented separately within weapon-carrying and non-weapon-carrying groups.

Gambling perceptions

χ2 results on gambling perceptions are shown in Table 2. A range of 55.8%–71.1% weapon-carrying adolescents rated gambling prevention and non-permissive measures as important, whereas a range of 66.5%–90.8% was found in non-weapon-carriers. Weapon-carriers, compared to non-weapon-carriers, were more likely to rate parental oversight and non-involvement in gambling as not important including: not having access to Internet gambling at home, parent/guardian strictness about gambling, warnings from adults in family, learning about the risks of gambling from parents, having parents who do not gamble, adults not involving kids in gambling, and parent/guardian not permitting card games at home. Weapon-carriers were also more likely to rate environmental context and peer non-involvement in gambling as not important including: checking identification for purchasing lottery tickets; participating in activities that are fun and free of gambling; advertisements that show the problems associated with gambling; learning about the risk of gambling in school; hanging out with friends who do not gamble; warnings from, or listening to, peers; and learning about risks of gambling from peers. In addition, weapon-carriers reported greater parental approval of adolescent gambling and having concern for a close family member’s gambling.

Table 2.

Gambling-related perceptions and attitudes in weapon-carrying and non-weapon-carrying adolescents

Non-weapon-carryingWeapon-carrying
VariableN%N%χ2p
Perceived parental perception of gambling50.4<.0001
 Disapprove63644.417534.9
 Neither approve nor disapprove69448.423747.2
 Approve1047.39017.9
Importance for preventing gambling problems in teens
 Checking identification for purchasing lottery tickets59.98<.0001
  Not important24815.416930.5
  Important1,36184.638669.5
Hanging out with friends who do not gamble44.21<.0001
 Not important38223.921338.7
 Important1,21376.133861.3
Participating in activities that are fun and free of gambling80.4<.0001
 Not important23814.917832.5
 Important1,35784.837067.5
Fear of losing valuable possessions, close friends, and relatives
 Not important1479.212622.968.35<.0001
 Important1,44490.842577.1
Advertisements that show the problems associated with gambling
 Not important32720.720136.755.59<.0001
 Important1,25279.334763.3
Not having access to Internet gambling at home33.35<.0001
 Not important52232.925546.7
 Important1,06467.129153.3
Parent/guardian strictness about gambling47.53<.0001
 Not important28217.817431.8
 Important1,30382.237368.2
Warning from adults in family52.39<.0001
 Not important28117.817732.5
 Important1,30282.236767.5
Warning from, or listening to, peers68.07<.0001
 Not important25616.217932.8
 Important1,32083.936767.2
Having parents who do not gamble65.19<.0001
 Not important29118.419235.2
 Important1,29281.635464.8
Learning about the risks of gambling in school53.62<.0001
 Not important33921.520437.3
 Important1,24178.534362.7
Learning about the risks of gambling from parents63.53<.0001
 Not important25816.317632.2
 Important1,32583.737067.8
Learning about the risks of gambling from peers48.73<.0001
 Not important31419.919034.5
 Important1,26780.136065.5
Adults not involving kids in gambling83.88<.0001
 Not important23514.918032.9
 Important1,34385.136767.1
Parent/guardian not permitting card games (for money) at home20.09<.0001
 Not important52933.524244.2
 Important1,05166.530655.8
Family concern9.440.0021
 No1,38788.445383.3
 Yes18211.69116.7

Health/functioning measures

Logistic and multinomial logistic regression analyses of health/functioning data are shown in Table 3. Among weapon-carrying adolescents, those with ARPG compared to NG were more likely to report smoking tobacco regularly (p = .04) and heavy current alcohol use (p = .02). Within non-weapon-carriers, those with LRG and ARPG compared to NG were more likely to report lifetime marijuana use (both p < .001), smoking tobacco occasionally (p = .001; p < .001) and regularly (p = .01; p = .002), lifetime alcohol use (both p < .001), and moderate (p = .03; p = .04) and heavy alcohol use (p = .03; p = .04). Non-weapon-carriers with ARPG compared to NG were more likely to report lifetime other drug use (p = .004). The proportion of health/functioning responses for each gambling group stratified by weapon-carrying status is shown in Table 4. Group differences were found for extracurricular activities and lifetime marijuana and other drug use for weapon-carriers and non-weapon-carriers, current smoking, and alcohol use in non-weapon-carriers, and dysphoria/depression in weapon-carriers.

Table 3.

Multivariate-adjusted analyses of problem gambling severity and health/functioning measures stratified by weapon-carrying status

Non-weapon-carryingWeapon-carryingInteraction OR (WC vs. NWC)
LRG vs. NGARPG vs. NGLRG vs. NGARPG vs. NGLRG vs. NGARPG vs. NG
VariableOR[95% CI]OR[95% CI]OR[95% CI]OR[95% CI]OR[95% CI]OR[95% CI]
Extracurricular activities1.40*[1.05–1.87]1.88***[1.28–2.77]2.19*[1.07–4.49]2.01[0.97–4.16]1.51[0.71–3.22]1.26[0.56–2.80]
Grade average
 A’s and B’sRef.Ref.Ref.Ref.Ref.Ref.
 Mostly C’s1.14[0.84–1.53]1.50*[1.01–2.10]1.73[0.76–3.97]1.64[0.71–3.82]1.54[0.64–3.70]1.11[0.45–2.74]
 D’s or lower0.84[0.53–1.31]1.37[0.81–2.33]1.32[0.53–3.29]1.65[0.66–4.13]1.58[0.57–4.33]1.14[0.40–3.24]
Substance use
 Marijuana use, lifetime1.75***[1.29–2.37]2.31***[1.60–3.33]0.79[0.36–1.71]1.6[0.73–3.53]0.45[0.20–1.03]0.72[0.31–1.7]
 Other drug use, lifetime1.96[0.96–3.99]3.26**[1.47–7.22]1.12[0.44–2.84]2.21[0.88–5.58]0.59[0.18–1.90]0.64[0.19–2.11]
Smoking, current
 NeverRef.Ref.Ref.Ref.Ref.Ref.
 Occasionally1.79***[1.27–2.52]2.88***[1.92–4.32]1.07[0.46–2.50]1.61[0.68–3.81]0.63[0.25–1.55]0.66[0.26–1.68]
 Regularly1.89**[1.18–3.02]2.48**[1.40–4.37]1.27[0.49–3.25]2.69*[1.04–6.98]0.67[0.23–1.91]1.06[0.36–3.16]
Alcohol use, lifetime3.87***[2.72–5.49]4.10***[2.58–6.52]2.08[0.54–8.04]1.65[0.44–6.23]0.63[0.16–2.57]0.57[0.14–2.31]
Alcohol use, current
 Never regularRef.Ref.Ref.Ref.Ref.Ref.
 Light1.23[0.76–1.98]1.33[0.75–2.37]1.73[0.48–6.19]3.05[0.82–11.31]1.39[0.357–5.38]2.05[0.50–8.41]
 Moderate1.75*[1.04–2.94]1.91*[1.03–3.54]1.44[0.46–4.53]3.16[0.97–10.24]0.84[0.24–2.92]1.60[0.43–5.90]
 Heavy3.61*[1.10–6.20]3.45**[1.50–10.43]2.93[0.57–14.97]7.18*[1.38–37.52]1.14[0.18–7.25]1.88[0.28–12.57]
Dysphoria/depression1.3[0.93–1.82]2.39***[1.57–3.62]0.62[0.28–1.39]1.23[0.55–2.74]0.48[0.20–1.14]0.51[0.21–1.25]
Body mass index
 UnderweightRef.Ref.Ref.Ref.Ref.Ref.
 Lean0.93[0.60–1.45]0.95[0.53–1.69]0.35[0.043–2.80]0.23[0.03–1.85]0.34[0.04–2.87]0.25[0.03–2.12]
 Overweight0.63[0.37–1.07]0.82[0.42–1.61]0.52[0.06–4.90]0.28[0.03–2.69]0.74[0.07–7.44]0.32[0.03–3.37]
 Obese0.83[0.41–1.68]1.21[0.51–2.84]0.47[0.04–5.84]0.25[0.02–3.15]0.55[0.04–7.46]0.25[0.02–3.57]

Note. ARPG: at-risk/problem gambling; LRG: low-risk gambling; NG: non-gambling; WC: weapon-carrying; NWC: non-weapon-carrying; OR: odds ratio; Reference Category: Non-Gambling Group.

*p ≤ .05. **p ≤ .01. ***p ≤ .001.

Table 4.

χ2 analyses of problem gambling severity and health/functioning proportions stratified by weapon-carrying status

Non-weapon-carryingχ2pWeapon-carryingχ2p
NGLRGARPGNGLRGARPG
VariableN%N%N%N%N%N%
Any extracurricular activities25871.375877.329080.69.2.012147.719671.521175.113.96.001
Grade average13.35.014.92.300
 A’s and B’s22964.959662.318753.42046.59836.79535.2
 Mostly C’s8918.128157.212134.61125.610840.410037
 D’s or lower359.9808.442121227.96122.87527.8
Substance use
 Marijuana use, lifetime8425.134837.914242.825.06<.0012666.715257.619371.711.8.003
 Other drug use, lifetime113.7496.42710.19.77.01926.55323.88435.78.05.020
Smoking, current27.47<.0019.06.060
 Never26676.261463.620658.91640111428330.9
 Occasionally5616.023123.910229.112308431.88933.1
 Regularly277.712112.5421212306926.19736.1
Alcohol use, lifetime23469.482088.729186.671.1<.0013992.924695.325594.40.54.760
Alcohol use, current11.66.077.86.250
 Never regular5440.319430.26426.810405426.23618.9
 Light4231.318929.47330.54165024.34423.2
 Moderate3123.119430.27330.56246230.16333.2
 Heavy75.26610.32912.15204019.44724.7
Dysphoria/depression6519.119520.98224.22.8.2513315822.48733.58.03.020
Body mass index8.56.203.82.700
 Underweight3611.49811.1299.112.7177.1219.3
 Lean20464.860869.020363.82773.015263.114764.8
 Overweight5617.812414.16219.5718.95020.73917.2
 Obese196515.8247.525.4229.1208.8

Note. ARPG: at-risk/problem gambling; LRG: low-risk gambling; NG: non-gambling.

Both weapon-carrying and non-weapon-carrying adolescents with LRG compared to NG were more likely to report having extracurricular activities (p = .03; p = .02), while non-weapon-carrying adolescents with ARPG compared to NG were more likely to report extracurricular activities (p = .001). Non-weapon-carriers with ARPG compared to NG were more likely to report a grade average of mostly C’s (p = .04) and dysphoria/depression (p < .001). No significant interactions between weapon-carrying status and problem gambling severity were found. The proportions of substance use behaviors for each problem gambling criteria level stratified by weapon-carrying status are shown in Table 5. Among weapon-carriers and non-weapon-carriers, problem gambling severity levels were associated with greater frequencies of lifetime marijuana and other drug use (all ps < .01). In addition, symptom levels were associated with greater proportions of smoking tobacco regularly in weapon-carriers (p < .001).

Table 5.

χ2 analyses of problem gambling criteria levels and substance use proportions by weapon-carrying status

Non-weapon-carryingχ2pWeapon-carryingχ2p
0 criteria1–2 criteria3–4 criteria≥5 criteria0 criteria1–2 criteria3–4 criteria≥5 criteria
Substance useN%N%N%N%N%N%N%N%
Marijuana use, lifetime34837.99137.92949.22266.713.67.00315257.68761.73572.97188.828.1<.001
Other drug use, lifetime496.4115.9816.7823.520.92<.0015323.82318.91534.14666.755.9<.001
Smoking, current7.09.3146.03<.001
 Never61463.615159.73556.52057.1111425639.71531.31215
 Occasionally23123.97328.92133.9822.98431.85438.31633.31923.8
 Regularly12112.52911.569.77206926.13122.01735.44961.3
Alcohol use, lifetime82088.720887.45286.73181.62.14.5424695.313395.04693.97693.80.41.94
Alcohol use, current15.27.0813.34.15
 Never regular19430.25229.4921.4315.05426.22420.5823.5410.3
 Light18929.45631.61228.6525.05024.33025.6411.81025.6
 Moderate19430.25229.41638.1525.06230.14135.01132.41128.2
 Heavy6610.3179.6511.9735.04019.42218.81112.61435.9

Note. Criteria: criteria level for problem gambling.

Gambling characteristics

The results of logistic and multinomial logistic regression analysis of gambling characteristics data are shown in Table 6. Among both weapon-carrying and non-weapon-carrying adolescents, ARPG compared to LRG group was more likely to report: non-strategic gambling (p = .02; p = .03), machine gambling (p < .001; p = .01), online gambling (all ps < .001), gambling on school grounds (both p < .001), casino gambling (both p < .001), pressure as a trigger for gambling (both p < .001), anxiety as a trigger for gambling (both p < .001), gambling for excitement (both p < .001), financial reasons (both p < .001), escape (both p < .001) and social reasons (p = .02; p < .001), and gambling for ≥2 hr per week (both p < .001).

Table 6.

Multivariate-adjusted analyses of problem gambling severity and gambling characteristics stratified by weapon-carrying status

Non-weapon-carryingWeapon-carryingInteraction OR [WC vs. NWC]
ARPG vs. LRGARPG vs. LRGARPG vs. LRG
VariableOR[95% CI]OR[95% CI]Interaction OR[95% CI]
Gambling types
 Strategic2.13*[1.13–4.01]1.00[0.46–2.20]0.51[0.19–1.34]
 Non-strategic1.37*[1.03–1.81]1.66*[1.10–2.48]1.20[0.75–1.93]
 Machine1.56**[1.15–2.13]3.56***[2.25–5.41]2.17**[1.31–3.60]
Gambling locations
 Online2.68***[1.92–3.74]3.64***[1.75–4.00]0.92[0.55–1.55]
 School4.66***[3.46–6.28]3.19***[2.14–4.74]0.74[0.45–1.21]
 Casino3.86***[1.74–4.68]5.15***[2.86–9.29]1.70[0.81–3.57]
Triggers for gambling
 Pressure2.97***[1.87–4.71]8.70***[3.95–19.16]2.38[0.97–5.80]
 Anxiety20.27***[6.80–60.42]10.22***[4.19–24.95]0.45[0.11–1.78]
Reasons for gambling
 Excitement3.40***[2.57–4.49]3.18***[2.18–4.63]0.98[0.62–1.55]
 Financial reasons3.39***[2.54–4.42]2.78***[1.87–4.12]0.84[0.52–1.36]
 Escape11.80***[4.87–28.59]6.03***[2.70–13.46]0.47[0.15–1.50]
 Social reasons1.86***[1.41–2.45]1.55*[1.07–2.240.82[0.52–1.29]
Gambling partners
 Family1.55**[1.18–2.03]0.86[0.59–1.25]0.57*[0.36–0.90]
 Friends2.41***[1.71–3.40]0.94[0.61–1.45]0.37***[0.22–0.64]
 Other adults3.64***[2.47–5.37]1.41[0.90–2.22]0.37***[0.21–0.67]
 Strangers5.92***[3.29–10.66]3.51***[1.99–6.21]0.63[0.28–1.39]
 Alone4.52***[2.77–7.38]2.57**[1.37–4.81]0.66[0.31–1.43]
Weekly time spent gambling
 1 hr or lessRef.Ref.Ref.
 ≥2 hr6.06***[3.93–9.37]3.39***[2.12–5.42]0.55[0.29–1.03]
Age of onset of gambling
 ≤8 years oldRef.Ref.Ref.
 9–11 years old1.08[0.62–1.86]0.99[0.54–1.81]0.87[0.39–1.93]
 12–14 years old0.67[0.41–1.09]0.95[0.57–1.61]1.36[0.68–2.73]
 ≥15 years old0.63[0.38–1.03]0.53*[0.28–0.99]0.83[0.39–1.80]

Note. ARPG: at-risk/problem gambling; LRG: low-risk gambling; WC: weapon-carrying; NWC: non-weapon-carrying; OR: odds ratio; CI: confidence interval; Reference category: low-risk gambling.

*p ≤ .05. **p ≤ .01. ***p ≤ .001.

Among non-weapon-carrying adolescents, the ARPG relative to the LRG group was more likely to report: strategic gambling (p = .02) and gambling with family (p = .002), friends (p < .001), other adults (p < .001), strangers (p < .001), and alone (p < .001). In weapon-carriers, the ARPG relative to the LRG group was more likely to report gambling with strangers (p < .001) and alone (p = .003). In addition, weapon-carriers with APRG compared to LRG were less likely to report gambling initiation at ages ≥15 years old (p = .05). Significant interactions between weapon-carrying status and problem gambling severity were found for: gambling with family (p = .02), friends (p < .001), and other adults (p = .001) and machine gambling (p = .003). After inverse-transforming ORs less than 1 (1/OR), weapon-carriers with ARPG versus those with LRG were 1.75 [1/(OR = 0.57)] times less likely to gamble with family, and 2.7 [1/(OR = 0.37)] times less likely to gamble with friends or other adults, relative to non-weapon-carriers.

Whereas a greater likelihood of weapon-carrying has been observed in boys (Pickett et al., 2005), gambling behaviors in male adolescents showed similar interactions between problem gambling severity and weapon-carrying (Supplementary Table S1). Weapon-carrying with ARPG as compared to weapon-carrying with LRG was 2.15 times more likely to be associated with machine gambling, and 1.72 [1/(OR = 0.58)], 3.8 [1/(OR = 0.26)], and 2.8 [1/(OR = 0.36)] times less likely to be associated with gambling with family, friends, or other adults, respectively.

Discussion and Conclusions

A recent call to action highlighted the critical importance for understanding the relationship between problem gambling and violence and advocated for greater support for research in prevention of health and behavioral risks associated with gambling (Weinstock, 2018). This is one of the first studies, to our knowledge, that investigated self-reported gambling perceptions, gambling characteristics and health/functioning correlates, of problem gambling severity among adolescents who endorsed or denied carrying a weapon, as well as the interaction effects between weapon-carrying and problem gambling severity in behavioral correlates. In line with the first hypothesis, weapon-carrying status was associated with problem gambling severity, with a larger proportion endorsing ARPG among weapon-carrying adolescents, relative to non-weapon-carrying adolescents. Supporting the second hypothesis, weapon-carriers had more permissive perceptions of gambling, and a larger proportion rated prevention methods as not important, relative to non-weapon-carriers. The third hypothesis was partially supported as the associations between problem gambling severity and several gambling characteristics, but not health/functioning measures, were different among weapon-carriers and non-weapon-carriers.

The association between problem gambling severity and weapon-carrying is consistent with previous studies of adolescents (Cook et al., 2015; Goldstein et al., 2009; Potenza et al., 2011; Slavin et al., 2013). Weapon-carrying in youth has been suggested to indicate “violent lifestyles” that include substance use, violence, and antisocial behavior as described by the problem behavior theory (Jessor & Jessor, 1977; Pickett et al., 2005). Whether weapon-carrying directly supports the development of gambling habits or whether problem gambling promotes violence including weapon-carrying to manage the consequences of gambling behaviors (or other possibilities) is unclear. Previous research on the relationship between problem gambling and criminal activity suggested that individuals with gambling problems may engage in illegal acts to support gambling (Adolphe, Khatib, van Golde, Gainsbury, & Blaszczynski, 2019; Mishra et al., 2011; Turner, Preston, Saunders, McAvoy, & Jain, 2009). As criminal activities often involve delinquent and antisocial behaviors (Magoon, Gupta, & Derevensky, 2005), it is possible that adolescents initiate weapon-carrying consequent to existing problem gambling to maintain gambling behaviors. However, further research is necessary to elucidate the pathway between weapon-carrying and problem gambling and possible gambling-related motivations for weapon-carrying.

ARPG and weapon-carrying may also be associated through overlapping determinants of problem behaviors. Problem gambling has previously been shown to co-occur with antisocial personality disorder and conduct disorder, and their association was predominately explained by common genetic factors (Slutske et al., 2001). Both problem gambling and antisocial behavior have been individually associated with impulsivity (Leeman & Potenza, 2012; Moffitt, Caspi, Harrington, & Milne, 2002), and significant proportions of variance in gambling, problem gambling, and antisocial behavior have been explained by risk-accepting tendencies including impulsivity, sensation seeking, and poor self-control (Mishra et al., 2011). Inasmuch as behavioral regulation develops throughout adolescence, findings from the National Longitudinal Study of Adolescent Health indicated that weapon-carrying likelihood was highest during age 15–17 years, and declined by age 18–21 years (Kodjo, Auinger, & Ryan, 2003). This is consistent with this study findings of lower weapon-carrying likelihoods in Grade 12 students. Similarly, previous reports on our sample demonstrated that early-onset gambling (prior to 12 years old) was associated with a higher likelihood of ARPG (43%) relative to later-onset gambling (32%; Rahman et al., 2012).

Weapon-carrying adolescents reported more permissive attitudes toward gambling across multiple measures. Of note, a lower proportion of weapon-carrying adolescents rated methods that involved parents not engaging in and not exposing children to gambling as not important in preventing gambling problems. Adolescents who perceive family members as participating in, and being more permissive of, gambling may themselves regard gambling as more acceptable and less harmful, which may increase the risk of problem gambling (Campbell, Derevensky, Meerkamper, & Cutajar, 2011; Zhai et al., 2017). We found that weapon-carrying adolescents were less likely to report having parents who disapproved of gambling and more likely to report having a family member with concerning levels of gambling. It is possible that perceptions of permissive attitudes toward gambling and modeling of gambling behaviors by parents may foster permissive attitudes toward similar gambling behaviors that co-occur with weapon-carrying in adolescents.

Parental permissive attitudes toward, and engagement in, gambling may be indicative of broader problems in parenting behavior. We found that a greater proportion of weapon-carriers rated parental monitoring and involvement items, including parent/guardian strictness about gambling and learning about the risk of gambling from parents, as not important. In addition to parental modeling of gambling behaviors, poorer monitoring of, lower trust of and poorer communication with adolescent children was previously associated with problem gambling severity (Magoon & Ingersoll, 2006). Weapon-carrying youth previously reported poorer parent–child relationships and permissive parenting including low parental monitoring and support (Calhoun, Glaser, Peiper, & Carr, 2015). More permissive and non-supportive parenting may foster development of permissive attitudes toward gambling among weapon-carrying adolescents, and amplify the risk of problem gambling. The relationship between weapon-carrying, parenting behavior, and gambling attitudes may be considered in the development of prevention programs for problem gambling. Inclusion of metrics for weapon-carrying, as well as permissive parenting behavior including low monitoring and involvement, may help identify youth at especially high risk of problem gambling. Emphasizing the importance of building strong parent–child relationships may be next steps for preventing co-occurring problem behaviors and risk of problem gambling.

The association between ARPG and gambling characteristics was similar between weapon-carrying and non-weapon-carrying adolescents with the exception of relationships with machine gambling and gambling with family, friends, and other adults. The association between ARPG and gambling with family, friends, and other adults was stronger in non-weapon-carriers compared to weapon-carriers. In contrast to non-weapon-carriers, the lack of associations between ARPG and gambling with familial and adult social partners in weapon-carriers suggests their problem gambling may be less influenced by social gambling, and rather contingent on asocial or solitary gambling. Indeed, gambling with strangers and alone were the only gambling-partner variables associated with ARPG in weapon-carrying adolescents. Although not statistically different from non-weapon carriers, the odds of gambling for social reasons were numerically lower among weapon-carriers with ARPG. Furthermore, the association between ARPG and machine gambling was significantly greater in weapon-carriers, compared to non-weapon-carriers. Engagement in machine gambling (e.g., playing slot machines, poker machines, or other gambling machines) as well as online gambling has been suggested to shift individuals from social to asocial forms of gambling and increase interindividual isolation (Griffiths, 1995, 1999). As gambling in severe problem gamblers was previously described as a “solitary activity,” it has been hypothesized that machine gambling and emerging electronic gambling technologies, through its asocial context, may increase gambling problems (Griffiths, 1995). The extent to which such solitary tendencies in conjunction with weapon-carrying and gambling problems may lay the foundation for current or future violent acts (e.g., intimate partner violence and shootings that have been linked to gambling, isolation, and access to weapons) requires further research (Roberts et al., 2018; Weinstock, 2018). Although it is important to note that different jurisdictions may have different regulations regarding gambling, there are often similarities in relationships between risk behaviors. Similar to alcohol use, gambling may occur at young ages. Within the US, 20%–86% middle- and high-school students previously gambled, especially on gambling machines (Jacobs, 2005). Reviews of international studies highlighted machine gambling as among the most prevalent gambling types in several countries, and this form was associated with more gambling-related problems (Calado, Alexandre, & Griffiths, 2017).

On the whole, the results suggest that weapon-carrying adolescents may represent a high-risk subgroup for ARPG characterized by asocial behavior. Important next steps for problem gambling and violence prevention may focus on the importance of building supportive relationships with family and peer groups and education on risky social contexts. Future problem gambling assessments may also include weapons involvement to explore the underlying core features shared by gambling and violence. These findings may inform preventions including mindfulness-based therapies that may reduce the risk of gambling problems and violence (de Lisle, Dowling, & Sabura Allen, 2011; Kelley & Lambert, 2012).

The study has multiple strengths and limitations. Given the numbers of adolescent participants in each problem-gambling-severity-by-weapon-carrying group, power to detect certain interactions between a large numbers of factors at once is limited. The weapon-carrying measure did not differentiate between types of weapons or weapon-carrying locations (e.g., school and public), and did not account for whether weapon-carrying was related to bullying victimization or perpetration. Participants may be unwilling to report sensitive information on victimization and perpetration related to weapon-carrying. Recent evidence indicated that cyberbullying perpetration, but not victimization, was related to weapon-carrying 1 year later, while weapon-carrying prospectively predicted cyberbullying victimization, but not perpetration (Lu et al., 2019). Data from other reporters including parents were not available to verify self-reports. However, adolescents may not disclose sensitive information, including weapon-carrying, and report from others may not be particularly accurate. It is thus important for future research to examine weapon-carrying motivations and contexts as related to adolescent problem gambling severity. While the sample was collected from schools across Connecticut, generalizability to national or international contexts is limited. The data were collected in 2006, during a different gambling environment. The findings, however, may provide an important historical context for additional studies examining more current assessments of gambling behavior and perceptions, weapon-carrying, and health/functioning, which also are needed. Furthermore, the cross-sectional data limit elucidation of directional pathways between weapon-carrying, problem gambling severity, and their correlates. Longitudinal data will be needed to further explicate the mechanisms underlying the co-occurrence of weapon-carrying and problem gambling.

This is one of the first studies to demonstrate that weapon-carrying adolescents exhibited more permissive attitudes toward gambling, and had stronger associations between ARPG and machine gambling and weaker associations between ARPG and familial and peer gambling partners, compared to non-weapon-carrying adolescents. These findings reinforce the need to better understand the impact of social contexts and family–child relationships in the etiology of problem gambling and weapon-related violence. Prevention efforts in schools and communities that bolster secure relationships between adolescents and parents, and normative peers, and protect against solitary/asocial behaviors may be important for ameliorating risks of problem gambling and weapon-carrying.

Authors’ contribution

Drs. RAH, SK-S, and MNP designed the survey with Dr. MAS advising on the inclusion of gambling-related questions. Dr. ZWZ and Ms. CFM conducted analyses and worked with Dr. MNP to develop initial drafts of the manuscript. All authors provided critical feedback with respect to the content of the manuscript. They also had full access to all data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Conflict of interest

The authors report no conflicts of interest with respect to the content of this manuscript. Dr. MNP has consulted for and advised Shire, INSYS Rivermend Health, Opiant/Lakelight Therapeutics, and Jazz Pharmaceuticals; received research support from the National Institutes of Health, Mohegan Sun Casino, and the National Center for Responsible Gaming; participated in surveys, mailings, or telephone consultations related to drug addiction, impulse-control disorders, or other health topics; consulted for law offices and the federal public defender’s office in issues related to impulse-control and addictive disorders; provided clinical care in the Connecticut Department of Mental Health and Addiction Services Problem Gambling Services Program; performed grant reviews for the National Institutes of Health and other agencies; edited journals and journal sections; given academic lectures in grand rounds, CME events, and other clinical/scientific venues; and generated books or chapters for publishers of mental health texts. Other authors report no disclosures. The views presented in this manuscript represent those of the authors and not necessarily those of the funding agencies.

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  • Muula, A. S., Rudatsikira, E., & Siziya, S. (2008). Correlates of weapon carrying among high school students in the United States. Annals of General Psychiatry, 7(1), 8. doi:10.1186/1744-859X-7-8

    • Crossref
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  • Pickett, W., Craig, W., Harel, Y., Cunningham, J., Simpson, K., Molcho, M., Mazur, J., Dostaler, S., Overpeck, M. D., & Currie, C. E. (2005). Cross-national study of fighting and weapon carrying as determinants of adolescent injury. Pediatrics, 116(6), e855e863. doi:10.1542/peds.2005-0607

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  • Pickett, W., Schmid, H., Boyce, W. F., Simpson, K., Scheidt, P. C., Mazur, J., Molcho, M., King, M. A., Godeau, E., Overpeck, M., Aszmann, A., Szabo, M., & Harel, Y. (2002). Multiple risk behavior and injury: An international analysis of young people. Archives of Pediatrics and Adolescent Medicine, 156(8), 786793. doi:10.1001/archpedi.156.8.786

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  • Pilver, C. E., Libby, D. J., Hoff, R. A., & Potenza, M. N. (2013a). Gender differences in the relationship between gambling problems and the incidence of substance-use disorders in a nationally representative population sample. Drug and Alcohol Dependence, 133(1), 204211. doi:10.1016/j.drugalcdep.2013.05.002

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  • Pilver, C. E., Libby, D. J., Hoff, R. A., & Potenza, M. N. (2013b). Problem gambling severity and the incidence of Axis I psychopathology among older adults in the general population. Journal of Psychiatric Research, 47(4), 534541. doi:10.1016/j.jpsychires.2012.12.013

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  • Potenza, M. N., Wareham, J. D., Steinberg, M. A., Rugle, L., Cavallo, D. A., Krishnan-Sarin, S., & Desai, R. A. (2011). Correlates of at-risk/problem Internet gambling in adolescents. Journal of the American Acadademy of Child and Adolescent Psychiatry, 50(2), 150159.e3. doi:10.1016/j.jaac.2010.11.006

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  • Proimos, J., DuRant, R. H., Pierce, J. D., & Goodman, E. (1998). Gambling and other risk behaviors among 8th- to 12th-grade students. Pediatrics, 102(2), e23. doi:10.1542/peds.102.2.e23

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  • Rahman, A. S., Pilver, C. E., Desai, R. A., Steinberg, M. A., Rugle, L., Krishnan-Sarin, S., & Potenza, M. N. (2012). The relationship between age of gambling onset and adolescent problematic gambling severity. Journal of Psychiatric Research, 46(5), 675683. doi:10.1016/j.jpsychires.2012.02.007

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    • Search Google Scholar
    • Export Citation
  • Roberts, A., Landon, J., Sharman, S., Hakes, J., Suomi, A., & Cowlishaw, S. (2018). Gambling and physical intimate partner violence: Results from the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC). The American Journal on Addictions, 27(1), 714. doi:10.1111/ajad.12656

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    • Export Citation
  • Ruggles, K. V., & Rajan, S. (2014). Gun possession among American youth: A discovery-based approach to understand gun violence. PLoS One, 9(11), e111893. doi:10.1371/journal.pone.0111893

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  • Schepis, T. S., Desai, R. A., Smith, A. E., Cavallo, D. A., Liss, T. B., McFetridge, A., Potenza, M. N., & Krishnan-Sarin, S. (2008). Impulsive sensation seeking, parental history of alcohol problems, and current alcohol and tobacco use in adolescents. Journal of Addiction Medicine, 2(4), 185193. doi:10.1097/ADM.0b013e31818d8916

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  • Shaffer, H. J., Labrie, R., Scanlan, K. M., & Cummings, T. N. (1994). Pathological gambling among adolescents: Massachusetts Gambling Screen (MAGS). Journal of Gambling Studies, 10(4), 339362. doi:10.1007/BF02104901

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    • Export Citation
  • Slavin, M., Pilver, C. E., Hoff, R. A., Krishnan-Sarin, S., Steinberg, M. A., Rugle, L., & Potenza, M. N. (2013). Serious physical fighting and gambling-related attitudes and behaviors in adolescents. Journal of Behavioral Addictions, 2(3), 167178. doi:10.1556/JBA.2.2013.009

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    • Export Citation
  • Slutske, W. S., Eisen, S., Xian, H., True, W. R., Lyons, M. J., Goldberg, J., & Tsuang, M. (2001). A twin study of the association between pathological gambling and antisocial personality disorder. Journal of Abnormal Psychology, 110(2), 297308. doi:10.1037/0021-843X.110.2.297

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    • Export Citation
  • Thurnherr, J., Michaud, P.-A., Berchtold, A., Akré, C., & Suris, J.-C. (2009). Youths carrying a weapon or using a weapon in a fight: What makes the difference? Health Education Research, 24(2), 270279. doi:10.1093/her/cyn017

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    • Export Citation
  • Turner, N. E., Preston, D. L., Saunders, C., McAvoy, S., & Jain, U. (2009). The relationship of problem gambling to criminal behavior in a sample of Canadian male federal offenders. Journal of Gambling Studies, 25(2), 153169. doi:10.1007/s10899-009-9124-1

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    • Export Citation
  • van Geel, M., Vedder, P., & Tanilon, J. (2014). Bullying and weapon carrying: A meta-analysis. JAMA Pediatrics, 168(8), 714720. doi:10.1001/jamapediatrics.2014.213

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  • Vitaro, F., Brendgen, M., Ladouceur, R., & Tremblay, R. E. (2001). Gambling, delinquency, and drug use during adolescence: Mutual influences and common risk factors. Journal of Gambling Studies, 17(3), 171190. doi:10.1023/A:1012201221601

    • Crossref
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    • Export Citation
  • Volberg, R. A., Gupta, R., Griffiths, M. D., Olason, D. T., & Delfabbro, P. (2010). An international perspective on youth gambling prevalence studies. Internatonal Journal of Adolescent Medicine and Health, 22(1), 338. doi:10.1515/IJAMH.2010.22.1.3

    • Search Google Scholar
    • Export Citation
  • Weinstock, J. (2018). Call to action for gambling disorder in the United States. Addiction, 113(6), 11561158. doi:10.1111/add.14225

  • Weinstock, J., Whelan, J. P., & Meyers, A. W. (2004). Behavioral assessment of gambling: An application of the timeline followback method. Psychological Assessment, 16(1), 7280. doi:10.1037/1040-3590.16.1.72

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  • Yip, S. W., Desai, R. A., Steinberg, M. A., Rugle, L., Cavallo, D. A., Krishnan-Sarin, S., & Potenza, M. N. (2011). Health/functioning characteristics, gambling behaviors, and gambling-related motivations in adolescents stratified by gambling problem severity: Findings from a high school survey. The American Journal on Addictions, 20(6), 495508. doi:10.1111/j.1521-0391.2011.00180.x

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    • Search Google Scholar
    • Export Citation
  • Zhai, Z. W., Yip, S. W., Steinberg, M. A., Wampler, J., Hoff, R. A., Krishnan-Sarin, S., & Potenza, M. N. (2017). Relationships between perceived family gambling and peer gambling and adolescent problem gambling and binge-drinking. Journal of Gambling Studies, 33(4), 11691185. doi:10.1007/s10899-017-9670-x

    • Crossref
    • Search Google Scholar
    • Export Citation

Supplementary Materials

  • Adolphe, A., Khatib, L., van Golde, C., Gainsbury, S. M., & Blaszczynski, A. (2019). Crime and gambling disorders: A systematic review. Journal of Gambling Studies, 35(2), 395414. doi:10.1007/s10899-018-9794-7

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  • Muula, A. S., Rudatsikira, E., & Siziya, S. (2008). Correlates of weapon carrying among high school students in the United States. Annals of General Psychiatry, 7(1), 8. doi:10.1186/1744-859X-7-8

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  • Pickett, W., Craig, W., Harel, Y., Cunningham, J., Simpson, K., Molcho, M., Mazur, J., Dostaler, S., Overpeck, M. D., & Currie, C. E. (2005). Cross-national study of fighting and weapon carrying as determinants of adolescent injury. Pediatrics, 116(6), e855e863. doi:10.1542/peds.2005-0607

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pickett, W., Schmid, H., Boyce, W. F., Simpson, K., Scheidt, P. C., Mazur, J., Molcho, M., King, M. A., Godeau, E., Overpeck, M., Aszmann, A., Szabo, M., & Harel, Y. (2002). Multiple risk behavior and injury: An international analysis of young people. Archives of Pediatrics and Adolescent Medicine, 156(8), 786793. doi:10.1001/archpedi.156.8.786

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pilver, C. E., Libby, D. J., Hoff, R. A., & Potenza, M. N. (2013a). Gender differences in the relationship between gambling problems and the incidence of substance-use disorders in a nationally representative population sample. Drug and Alcohol Dependence, 133(1), 204211. doi:10.1016/j.drugalcdep.2013.05.002

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pilver, C. E., Libby, D. J., Hoff, R. A., & Potenza, M. N. (2013b). Problem gambling severity and the incidence of Axis I psychopathology among older adults in the general population. Journal of Psychiatric Research, 47(4), 534541. doi:10.1016/j.jpsychires.2012.12.013

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Potenza, M. N., Wareham, J. D., Steinberg, M. A., Rugle, L., Cavallo, D. A., Krishnan-Sarin, S., & Desai, R. A. (2011). Correlates of at-risk/problem Internet gambling in adolescents. Journal of the American Acadademy of Child and Adolescent Psychiatry, 50(2), 150159.e3. doi:10.1016/j.jaac.2010.11.006

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Proimos, J., DuRant, R. H., Pierce, J. D., & Goodman, E. (1998). Gambling and other risk behaviors among 8th- to 12th-grade students. Pediatrics, 102(2), e23. doi:10.1542/peds.102.2.e23

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rahman, A. S., Pilver, C. E., Desai, R. A., Steinberg, M. A., Rugle, L., Krishnan-Sarin, S., & Potenza, M. N. (2012). The relationship between age of gambling onset and adolescent problematic gambling severity. Journal of Psychiatric Research, 46(5), 675683. doi:10.1016/j.jpsychires.2012.02.007

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Roberts, A., Landon, J., Sharman, S., Hakes, J., Suomi, A., & Cowlishaw, S. (2018). Gambling and physical intimate partner violence: Results from the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC). The American Journal on Addictions, 27(1), 714. doi:10.1111/ajad.12656

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ruggles, K. V., & Rajan, S. (2014). Gun possession among American youth: A discovery-based approach to understand gun violence. PLoS One, 9(11), e111893. doi:10.1371/journal.pone.0111893

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schepis, T. S., Desai, R. A., Smith, A. E., Cavallo, D. A., Liss, T. B., McFetridge, A., Potenza, M. N., & Krishnan-Sarin, S. (2008). Impulsive sensation seeking, parental history of alcohol problems, and current alcohol and tobacco use in adolescents. Journal of Addiction Medicine, 2(4), 185193. doi:10.1097/ADM.0b013e31818d8916

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Shaffer, H. J., Labrie, R., Scanlan, K. M., & Cummings, T. N. (1994). Pathological gambling among adolescents: Massachusetts Gambling Screen (MAGS). Journal of Gambling Studies, 10(4), 339362. doi:10.1007/BF02104901

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Slavin, M., Pilver, C. E., Hoff, R. A., Krishnan-Sarin, S., Steinberg, M. A., Rugle, L., & Potenza, M. N. (2013). Serious physical fighting and gambling-related attitudes and behaviors in adolescents. Journal of Behavioral Addictions, 2(3), 167178. doi:10.1556/JBA.2.2013.009

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Slutske, W. S., Eisen, S., Xian, H., True, W. R., Lyons, M. J., Goldberg, J., & Tsuang, M. (2001). A twin study of the association between pathological gambling and antisocial personality disorder. Journal of Abnormal Psychology, 110(2), 297308. doi:10.1037/0021-843X.110.2.297

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Thurnherr, J., Michaud, P.-A., Berchtold, A., Akré, C., & Suris, J.-C. (2009). Youths carrying a weapon or using a weapon in a fight: What makes the difference? Health Education Research, 24(2), 270279. doi:10.1093/her/cyn017

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Turner, N. E., Preston, D. L., Saunders, C., McAvoy, S., & Jain, U. (2009). The relationship of problem gambling to criminal behavior in a sample of Canadian male federal offenders. Journal of Gambling Studies, 25(2), 153169. doi:10.1007/s10899-009-9124-1

    • Crossref
    • Search Google Scholar
    • Export Citation
  • van Geel, M., Vedder, P., & Tanilon, J. (2014). Bullying and weapon carrying: A meta-analysis. JAMA Pediatrics, 168(8), 714720. doi:10.1001/jamapediatrics.2014.213

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Vitaro, F., Brendgen, M., Ladouceur, R., & Tremblay, R. E. (2001). Gambling, delinquency, and drug use during adolescence: Mutual influences and common risk factors. Journal of Gambling Studies, 17(3), 171190. doi:10.1023/A:1012201221601

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Volberg, R. A., Gupta, R., Griffiths, M. D., Olason, D. T., & Delfabbro, P. (2010). An international perspective on youth gambling prevalence studies. Internatonal Journal of Adolescent Medicine and Health, 22(1), 338. doi:10.1515/IJAMH.2010.22.1.3

    • Search Google Scholar
    • Export Citation
  • Weinstock, J. (2018). Call to action for gambling disorder in the United States. Addiction, 113(6), 11561158. doi:10.1111/add.14225

  • Weinstock, J., Whelan, J. P., & Meyers, A. W. (2004). Behavioral assessment of gambling: An application of the timeline followback method. Psychological Assessment, 16(1), 7280. doi:10.1037/1040-3590.16.1.72

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yip, S. W., Desai, R. A., Steinberg, M. A., Rugle, L., Cavallo, D. A., Krishnan-Sarin, S., & Potenza, M. N. (2011). Health/functioning characteristics, gambling behaviors, and gambling-related motivations in adolescents stratified by gambling problem severity: Findings from a high school survey. The American Journal on Addictions, 20(6), 495508. doi:10.1111/j.1521-0391.2011.00180.x

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhai, Z. W., Yip, S. W., Steinberg, M. A., Wampler, J., Hoff, R. A., Krishnan-Sarin, S., & Potenza, M. N. (2017). Relationships between perceived family gambling and peer gambling and adolescent problem gambling and binge-drinking. Journal of Gambling Studies, 33(4), 11691185. doi:10.1007/s10899-017-9670-x

    • Crossref
    • Search Google Scholar
    • Export Citation
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Dr. Zsolt Demetrovics
Institute of Psychology, ELTE Eötvös Loránd University
Address: Izabella u. 46. H-1064 Budapest, Hungary
Phone: +36-1-461-2681
E-mail: jba@ppk.elte.hu

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2020  
Total Cites 4024
WoS
Journal
Impact Factor
6,756
Rank by Psychiatry (SSCI) 12/143 (Q1)
Impact Factor Psychiatry 19/156 (Q1)
Impact Factor 6,052
without
Journal Self Cites
5 Year 8,735
Impact Factor
Journal  1,48
Citation Indicator  
Rank by Journal  Psychiatry 24/250 (Q1)
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Citable 86
Items
Total 74
Articles
Total 12
Reviews
Scimago 47
H-index
Scimago 2,265
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Scimago Clinical Psychology Q1
Quartile Score Psychiatry and Mental Health Q1
  Medicine (miscellaneous) Q1
Scopus 3593/367=9,8
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Scopus Clinical Psychology 7/283 (Q1)
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Scopus 2,026
SNIP  
Days from  38
sumbission  
to 1st decision  
Days from  37
acceptance  
to publication  
Acceptance 31%
Rate  

2019  
Total Cites
WoS
2 184
Impact Factor 5,143
Impact Factor
without
Journal Self Cites
4,346
5 Year
Impact Factor
5,758
Immediacy
Index
0,587
Citable
Items
75
Total
Articles
67
Total
Reviews
8
Cited
Half-Life
3,3
Citing
Half-Life
6,8
Eigenfactor
Score
0,00597
Article Influence
Score
1,447
% Articles
in
Citable Items
89,33
Normalized
Eigenfactor
0,7294
Average
IF
Percentile
87,923
Scimago
H-index
37
Scimago
Journal Rank
1,767
Scopus
Scite Score
2540/376=6,8
Scopus
Scite Score Rank
Cllinical Psychology 16/275 (Q1)
Medicine (miscellenous) 31/219 (Q1)
Psychiatry and Mental Health 47/506 (Q1)
Scopus
SNIP
1,441
Acceptance
Rate
32%

 

Journal of Behavioral Addictions
Publication Model Gold Open Access
Submission Fee none
Article Processing Charge 850 EUR/article
Printed Color Illustrations 40 EUR (or 10 000 HUF) + VAT / piece
Regional discounts on country of the funding agency World Bank Lower-middle-income economies: 50%
World Bank Low-income economies: 100%
Further Discounts Editorial Board / Advisory Board members: 50%
Corresponding authors, affiliated to an EISZ member institution subscribing to the journal package of Akadémiai Kiadó: 100%
Subscription Information Gold Open Access
Purchase per Title  

Journal of Behavioral Addictions
Language English
Size A4
Year of
Foundation
2011
Publication
Programme
2021 Volume 10
Volumes
per Year
1
Issues
per Year
4
Founder Eötvös Loránd Tudományegyetem
Founder's
Address
H-1053 Budapest, Hungary Egyetem tér 1-3.
Publisher Akadémiai Kiadó
Publisher's
Address
H-1117 Budapest, Hungary 1516 Budapest, PO Box 245.
Responsible
Publisher
Chief Executive Officer, Akadémiai Kiadó
ISSN 2062-5871 (Print)
ISSN 2063-5303 (Online)

Senior editors

Editor(s)-in-Chief: Zsolt DEMETROVICS

Assistant Editor(s): Csilla ÁGOSTON

Associate Editors

  • Judit BALÁZS (ELTE Eötvös Loránd University, Hungary)
  • Joel BILLIEUX (University of Lausanne, Switzerland)
  • Matthias BRAND (University of Duisburg-Essen, Germany)
  • Anneke GOUDRIAAN (University of Amsterdam, The Netherlands)
  • Daniel KING (Flinders University, Australia)
  • Ludwig KRAUS (IFT Institute for Therapy Research, Germany)
  • H. N. Alexander LOGEMANN (ELTE Eötvös Loránd University, Hungary)
  • Anikó MARÁZ (Humboldt University of Berlin, Germany)
  • Astrid MÜLLER (Hannover Medical School, Germany)
  • Marc N. POTENZA (Yale University, USA)
  • Hans-Jurgen RUMPF (University of Lübeck, Germany)
  • Attila SZABÓ (ELTE Eötvös Loránd University, Hungary)
  • Róbert URBÁN (ELTE Eötvös Loránd University, Hungary)
  • Aviv M. WEINSTEIN (Ariel University, Israel)

Editorial Board

  • Max W. ABBOTT (Auckland University of Technology, New Zealand)
  • Elias N. ABOUJAOUDE (Stanford University School of Medicine, USA)
  • Hojjat ADELI (Ohio State University, USA)
  • Alex BALDACCHINO (University of Dundee, United Kingdom)
  • Alex BLASZCZYNSKI (University of Sidney, Australia)
  • Kenneth BLUM (University of Florida, USA)
  • Henrietta BOWDEN-JONES (Imperial College, United Kingdom)
  • Beáta BÖTHE (University of Montreal, Canada)
  • Wim VAN DEN BRINK (University of Amsterdam, The Netherlands)
  • Gerhard BÜHRINGER (Technische Universität Dresden, Germany)
  • Sam-Wook CHOI (Eulji University, Republic of Korea)
  • Damiaan DENYS (University of Amsterdam, The Netherlands)
  • Jeffrey L. DEREVENSKY (McGill University, Canada)
  • Naomi FINEBERG (University of Hertfordshire, United Kingdom)
  • Marie GRALL-BRONNEC (University Hospital of Nantes, France)
  • Jon E. GRANT (University of Minnesota, USA)
  • Mark GRIFFITHS (Nottingham Trent University, United Kingdom)
  • Heather HAUSENBLAS (Jacksonville University, USA)
  • Tobias HAYER (University of Bremen, Germany)
  • Susumu HIGUCHI (National Hospital Organization Kurihama Medical and Addiction Center, Japan)
  • David HODGINS (University of Calgary, Canada)
  • Eric HOLLANDER (Albert Einstein College of Medicine, USA)
  • Jaeseung JEONG (Korea Advanced Institute of Science and Technology, Republic of Korea)
  • Yasser KHAZAAL (Geneva University Hospital, Switzerland)
  • Orsolya KIRÁLY (Eötvös Loránd University, Hungary)
  • Emmanuel KUNTSCHE (La Trobe University, Australia)
  • Hae Kook LEE (The Catholic University of Korea, Republic of Korea)
  • Michel LEJOXEUX (Paris University, France)
  • Anikó MARÁZ (Eötvös Loránd University, Hungary)
  • Giovanni MARTINOTTI (‘Gabriele d’Annunzio’ University of Chieti-Pescara, Italy)
  • Frederick GERARD MOELLER (University of Texas, USA)
  • Daniel Thor OLASON (University of Iceland, Iceland)
  • Nancy PETRY (University of Connecticut, USA)
  • Bettina PIKÓ (University of Szeged, Hungary)
  • Afarin RAHIMI-MOVAGHAR (Teheran University of Medical Sciences, Iran)
  • József RÁCZ (Hungarian Academy of Sciences, Hungary)
  • Rory C. REID (University of California Los Angeles, USA)
  • Marcantanio M. SPADA (London South Bank University, United Kingdom)
  • Daniel SPRITZER (Study Group on Technological Addictions, Brazil)
  • Dan J. STEIN (University of Cape Town, South Africa)
  • Sherry H. STEWART (Dalhousie University, Canada)
  • Attila SZABÓ (Eötvös Loránd University, Hungary)
  • Ferenc TÚRY (Semmelweis University, Hungary)
  • Alfred UHL (Austrian Federal Health Institute, Austria)
  • Johan VANDERLINDEN (University Psychiatric Center K.U.Leuven, Belgium)
  • Alexander E. VOISKOUNSKY (Moscow State University, Russia)
  • Kimberly YOUNG (Center for Internet Addiction, USA)

 

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