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. Author manuscript; available in PMC: 2016 Dec 1.
Published in final edited form as: Addict Behav. 2015 Jul 17;51:57–64. doi: 10.1016/j.addbeh.2015.07.006

Correlates of gambling on high-school grounds

Dawn W Foster 1,2, Rani A Hoff 1, Corey E Pilver 3,4, Yvonne H C Yau 1, Marvin A Steinberg 5, Jeremy Wampler 6, Suchitra Krishnan-Sarin 1,2, Marc N Potenza 1,2,7
PMCID: PMC4558206  NIHMSID: NIHMS709045  PMID: 26232102

Abstract

Objective

This study examined adolescent gambling on school grounds (GS+) and how such behavior was associated with gambling-related attitudes. Further, we examined whether GS+ moderated associations between at-risk problem-gambling (ARPG) and gambling behaviors related to gambling partners.

Method

Participants were 1988 high-school students who completed survey materials. Demographic, perceptions, attitudes, and gambling variables were stratified by problem-gambling severity (ARPG versus recreational gambling) and GS+ status. Chi-square and adjusted logistic regression models were used to examine relationships among study variables.

Results

Nearly 40% (39.58%) of students reported past-year GS+, with 12.91% of GS+ students, relative to 2.63% of those who did not report gambling on school grounds (GS), meeting DSM-IV criteria for pathological gambling (p<0.0001). In comparison to GS- students, GS+ students were more likely to report poorer academic achievement and more permissive attitudes towards gambling behaviors. Weaker links in GS+ students, in comparison with GS-, students, were observed between problem-gambling severity and gambling with family members (interaction odds ratio (IOR)=0.60; 95%CI=0.39–0.92) and gambling with friends (IOR=0.21; 95%CI=0.11–0.39).

Conclusions

GS+ is common and associated with pathological gambling and more permissive attitudes towards gambling. The finding that GS+ (relative to GS-) youth show differences in how problem-gambling is related to gambling partners (friends and family) warrants further investigation regarding whether and how peer and familial interactions might be improved to diminish youth problem-gambling severity. The high frequency of GS+ and its relationship with ARPG highlight a need for school administrators and personnel to consider interventions that target school-based gambling.

Keywords: gambling, school, at-risk, adolescent

Introduction

High rates of gambling and gambling-related problems exist among adolescents (Barnes, Welte, Hoffman, & Tidwell, 2009; Volberg, Gupta, Griffiths, Olason, & Delfabbro, 2010; Yip et al., 2011). Although gambling is often viewed as an adult behavior, the prevalence of adolescent gambling problems is roughly three times that of adults (Shaffer, Hall, & Vander Bilt, 1999). Gambling during adolescence has been linked with psychiatric, social, and substance misuse problems in adulthood (Burge, Pietrzak, & Petry, 2006). Both recreational and problem gambling have been associated with adverse social functioning and mental health in adolescence including poor school performance and difficulties with aggression and mood (Lloyd et al., 2010; Yip et al., 2011). Thus, efforts to develop targeted educational, prevention, and intervention programs are in line with public and mental health initiatives.

Gambling-related perceptions have been linked to engagement in gambling (Foster, Neighbors, Rodriguez, Lazorwitz, & Gonzales, 2014; Leeman et al., 2014) and substance-use behaviors (Leeman et al., 2014). Extant literature related to adolescent perceptions about gambling indicates that perceptions of family and friends’ support for refraining against gambling may protect against problem gambling (Hardoon, Gupta, & Derevensky, 2004). However, adolescents who gamble with friends and peers may be at risk for gambling-related problems, particularly if gambling becomes a regular peer activity, as the behavior can become perceived as normative, safe, and even desirable (Shead, Derevensky, & Gupta, 2010). Furthermore, relative to non-problem gamblers, at-risk/problem gamblers are more likely to have friends who gamble, and are also more likely to approve of gambling behavior (Gori et al., 2014). Additionally, perceived norms for gambling (e.g., perceiving that gambling is prevalent among or more accepted by peers) have been tied to gambling behavior (Foster et al., 2014).

One domain in which youth may gamble or engage in other risk behaviors is within their school environment. Risk behaviors among students in school environments have been examined, including the use of alcohol (Hennessy & Tanner-Smith, 2014; Manthey, Aidoo, & Ward, 2008; Walters, Bennett, & Noto, 2000), tobacco (Agaku, Ayo-Yusuf, Vardavas, & Connolly, 2014; Cairney & Lawrance, 2002; Emory et al., 2014), and cannabis (Elliott & Carey, 2013) and engagement in gambling (Shaffer, Forman, Scanlan, & Smith, 2000). While being male and using substances have been linked to gambling and problem-gambling severity in high-school students (Lee, Martins, Pas, & Bradshaw, 2014; Yip et al., 2011), factors linked to the propensity to gamble on school grounds have not been systematically investigated. Given links between gambling and substance-use behaviors and peer influences on these processes (Langhinrichsen-Rohling, Rohde, Seeley, & Rohling, 2004), one might hypothesize that relationships between problem-gambling severity and gambling partners might be influenced by between gambling-on-school-grounds status. Given that schools have policies regarding not engaging in risk behaviors like gambling on school grounds, one might hypothesize that gambling-on-school-grounds status might be associated with more permissive attitudes towards gambling. Specific information regarding the factors associated with gambling on school grounds may provide school administrators, teachers and health-care providers (e.g., school nurses) important information regarding possible at-risk youth and individuals who might benefit from interventions.

Given the current gap in knowledge regarding relationships between gambling-on-school-grounds status, problem-gambling severity and gambling-related measures, the present study examined how gambling on school grounds might relate to at-risk problem gambling (ARPG) and gambling-related attitudes and behaviors. It was hypothesized that students who gambled on school grounds (GS+) as compared to those who did not (GS-) would be more likely to report poorer academic performance, more frequent ARPG and pathological gambling, and more permissive attitudes towards gambling. The study also examined the extent to which gambling-on-school-grounds status moderated the relationships between problem-gambling severity and substance use, Internet gambling, and reported gambling partners. Given that GS+ youth peers might be anticipated to be gambling with peers on school grounds, we hypothesized that gambling on school grounds would moderate the relationship between problem-gambling severity and gambling with peers.

Method

Participants and procedure

The present data came from a survey of risk behaviors among high-school students (Cavallo et al., 2010; Cavallo et al., 2010; Kundu et al., 2013; Slavin et al., 2013; Yau et al., 2014). All public four-year high-schools and nonvocational or special-education high-schools in the state of Connecticut were invited to participate in this research via invitation letters and follow-up phone calls during 2006–2007. Schools were offered follow-up reports of risk behavior frequencies in the student body as incentive for participation. Not all geographic regions of the state were adequately represented following initial recruitment procedures; thus, additional targeted recruitment was conducted in order to ensure sufficient representation of underrepresented regions. School board and/or superintendent permission was obtained among schools interested in participating. Schools from all geographic state regions and from each of the three distric-reference-group tiers (based on socioeconomic status of families within school districts) were included in the sample for a total of 4,523 adolescents. As the focus of the present analyses related to GS+ and problem-gambling severity, students who did not report having engaged in gambling behavior in the past year (12 months) were excluded as were those with missing information on inclusionary criteria for pathological gambling. Thus, the final sample consisted of 1,988 adolescents. The final sample did not differ from the total sample with regard to demographic characteristics or major study variables. Passive parental consent and student assent procedures were approved by the instituational review boards (IRB) at Yale University and all data collection sites.

Survey characteristics

The survey was designed to assess multiple risk behaviors among Connecticut high-school adolescents and was comprised of 154 questions assessing a range of demographic characteristics, gambling perceptions, problem-gambling severity, substance use, and other health and risk behaviors. Items were derived from surveys of adolescent risk behaviors such as the Youth Child Risk Behavior Survey (Eisenmann, Bartee, & Wang, 2002), and included previously established measures such as the Massachusetts Gambling Screen (MAGS; Shaffer, Labrie, Scanlan, & Cummings, 1994). Given the focus on GS+ and ARPG, only students reporting having engaged in gambling behavior and completing all scoring items from the MAGS were included in analyses.

Measures

Demographic characteristics

Participants provided demographic information including gender, age, racial/ethnic background, school grade, and grade average. Overall demographic findings have previously been published (Schepis et al., 2008; Yip et al., 2011).

Gambling on school grounds

Gambling was defined as “any game you bet on for money or anything else of value.” Gambling on school grounds was assessed by asking participants whether they had gambled on school grounds in the past year (12 months). Those endorsing Never were categorized as not gambling on school grounds (GS-) and those endorsing Less than monthly, Monthly, Weekly, or Daily were categorized as having gambled on school grounds (GS+).

Gambling perceptions

Perceptions related to gambling held by peers and family, as reported by participants, were assessed as described previously (Kundu et al., 2013; Slavin et al., 2013). Respondents indicated whether they thought their parents would disapprove or approve of their gambling (parental perception of gambling) on a Likert-type scale ranging from Strongly Disapprove to Strongly Approve. Responses were grouped into three categories: “Disapprove” (combining Strongly Disapprove and Disapprove), “Approve” (combining Strongly Approve and Approve), and “Neither approve nor disapprove.” Perception of problematic family gambling was assessed via the item “Has the gambling of a close family member caused you worry or concern?” with responses dichotomized to “yes/no.”

Attitudes towards preventing gambling problems among teens were assessed by asking respondents to indicate whether they felt each of 15 items was important or not important for “preventing gambling problems in people your age.” Example items include “Hanging out with friends who don’t gamble,” “Participating in activities that are fun and free of gambling,” and “Learning about the risks of gambling in school.” Responses were dichotomized as “important/not important.” Cronbach’s alpha was .93.

Substance use and Internet gambling

Lifetime substance use was assessed via the item, “Have you ever smoked a cigarette/marijuana/had a sip of alcohol/used designer or other drugs, such as Ecstacy, GHB, Special K, or cocaine?” Responses were dichotomized as “yes/no.” Alcohol use over the past 30 days was assessed among those who indicated having a sip of alcohol using the item, “During the past 30 days, on how many days did you have at least one drink of alcohol?” and responses were coded as “never” and “more than one.” Current caffeine use was assessed via the item “On average, how many servings of caffeine drinks do you drink a day?” and responses were coded as “none,” “1–2 drinks,” and “3 or more drinks per day.” Internet gambling was assessed using the item, “In the past 12 months, have you placed bets on the Internet?” and responses were dichotomized as “yes, no.”

Problem-gambling severity, substance use, Internet gambling and gambling partners

Problem-gambling severity was categorized as recreational gambling (past-year gambling but no inclusionary criteria for pathological gambling based on DSM-IV criteria) and ARPG (one or more past-year inclusionary criteria for pathological gambling based on DSM-IV criteria) as has been done previously (Hammond et al., 2014; Kong et al., 2013; Potenza et al., 2011; Rahman et al., 2014; Slavin et al., 2013). Cronbach’s alpha was .92. Tobacco use was assessed using the question, “Have you ever smoked a cigarette?,” with responses coded as never, occasionally and regularly as previously (Yip et al., 2011). Lifetime cannabis and other drug use were assessed via questions asking, “Have you ever smoked marijuana/used designer or other drugs, such as Ecstacy, GHB, Special K, or cocaine?” Responses were dichotomized as “yes/no.” Alcohol use over the past 30 days was assessed using the item, “During the past 30 days, on how many days did you have at least one drink of alcohol?” and responses were coded as Never Regular (1–5 days), Light (6–9 days), Moderate (10–19 days) and Heavy (20–30 days). Internet gambling was assessed using the item, “In the past 12 months, have you placed bets on the Internet?” and responses were dichotomized as “yes, no.” Gambling partners were categorized into gambling with family, adults, friend, alone, or stranger as was done previously (Yip et al., 2011).

Statistical analyses

Analyses were conducted using SAS 9.3. Chi-square tests were utilized to examine bivariate associations between GS+, GS-, and demographic characteristics. Chi-square tests were also used to examine whether GS+ and GS- differed in terms of ARPG, gambling-related perceptions, and attitudes. Next, multivariate-adjusted logistic regression models were conducted to examine associations between problem-gambling severity (ARPG and recreational gambling) and gambling partners separately for GS+ and GS-. Effects were evaluated in order to determine whether they differed across problem-gambling groups by fitting interaction models wherein interaction significance was determined by examining interaction odds ratios. Logistic regression models were adjusted for gender, race/ethnicity, grade level, grade average, and family structure. Statistical significance was determined using p values < .05 and confidence intervals (CIs) that did not include 1.

Results

Sociodemographic characteristics

Of the 1,988 adolescents whose data were included in present analyses, 790 (39.58%) reported gambling on school grounds (GS+) in the past 12 months, and 103 (5.18%) met criteria for pathological gambling. GS+ status was associated with gender, grade average, endorsement of “other” with respect to race/ethnicity, grade level, and family structure, but not with Caucasian, African-American, Asian, or Hispanic race/ethnicity (Table 1). GS+ status was associated with ARPG and pathological gambling in that 55.39% of those in the GS+ group, relative to 19.87% in the GS- group, reported ARPG (Table 1), and 12.91% in the GS+ group, relative to 2.63% in the GS- group, met DSM-IV criteria for pathological gambling (p<0.0001).

Table 1.

Socio-demographic characteristics of the sample by gambling on school grounds (GS) status

Variable Gambles on School Grounds (GS+) Does Not Gamble on School Grounds (GS-) χ2 p value
N % N %
Gender 254.50 <.0001
 Male 650 82.3 558 46.6
 Female 140 17.7 640 53.4
Race/Ethnicity
 Caucasian 0.26 .61
  Yes 579 72.6 871 71.5
  No 219 27.4 347 28.5
 African-American 0.09 .76
  Yes 94 11.8 138 11.3
  No 704 88.2 1080 88.7
 Asian 1.19 .27
  Yes 41 5.1 50 4.1
  No 757 94.86 1168 95.9
 Hispanic 0.15 .70
  Yes 122 16.2 197 16.9
  No 631 83.8 971 83.1
 Other 4.64 .03
  Yes 115 14.4 220 18.1
  No 683 85.6 998 81.9
Grade 15.60 .0014
 9th 221 27.7 382 31.5
 10th 191 24.0 339 28.0
 11th 211 26.5 299 25.0
 12th 174 21.8 191 15.8
Grade Average 34.76 <.0001
 A+B 349 45.2 670 56.8
 C 275 35.6 376 31.9
 D+F 149 19.3 133 11.3
Family Structure 9.77 .0076
 One parent 179 23.0 296 24.7
 Two parents 529 67.8 836 69.7
 Other 72 9.2 67 5.6
Problem-Gambling Severity 271.35 <.0001
 ARPG 442 55.4 242 19.9
 Recreational gambling 356 44.6 967 80.1
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Gambling-related perceptions and attitudes

Individuals categorized as GS+, as compared GS- individuals, were more likely to report perceptions of parental approval of gambling (Table 2). GS+ youth were more likely than GS- youth to view the following as less important for preventing gambling problems in peers: checking identification for purchasing lottery tickets; hanging out with friends who don’t gamble; participating in activities that are fun and free of gambling; fear of losing valuable possessions, close friends, and relatives; advertisements that show the problems associated with gambling; not having access to Internet gambling at home; parent/guardian strictness about gambling; gambling-related warnings from adults in the family; warnings from peers or listening to peers; having parents who don’t gamble; learning about the risks of gambling in school, from parents, and from peers; adults not involving children in gambling; and parent/guardian not permiting card games for money at home. GS+ youth, in comparison with GS- youth, were also less likely to report perceptions of problematic family gambling associated with the item, “Has the gambling of a close family member caused you worry or concern?”

Table 2.

Gambling-Related Perceptions and Attitudes

Variable Gambles on School Grounds (GS+) Does Not Gamble on School Grounds (GS-) χ2 p value Gambles on School Grounds (GS+) vs. Does not Gamble on School Grounds (GS-)
N % N % OR 95%
Parent perception of gambling 33.92 <.0001
 Disapprove 199 30.2 432 41.6 Ref --
 Neither approve nor disapprove 354 53.8 516 49.7 1.37 1.07–1.77
 Approve 105 16.0 90 8.7 2.49 1.69–3.66
Importance for preventing gambling problems in teens
Checking identification for purchasing lottery tickets 58.11 <.0001
 Important 514 69.8 969 84.5 Ref --
 Not important 222 30.2 177 15.5 0.49 0.37–0.63
Hanging out with friends who don’t gamble 59.09 <.0001
 Important 435 59.7 868 76.4 Ref --
 Not important 294 40.3 268 23.6 0.53 0.42–0.67
Participating in activities that are fun and free of gambling 53.16 <.0001
 Important 510 70.1 961 84.3 Ref --
 Not important 217 29.9 179 15.7 0.53 0.40–0.69
Fear of losing valuable possessions, close friends, and relatives 33.29 <.0001
 Important 588 80.5 1022 90.0 Ref --
 Not important 142 19.5 114 10.0 0.57 0.41–0.78
Advertisements that show the problems associated with gambling 65.61 <.0001
 Important 462 63.7 908 80.6 Ref --
 Not important 263 36.3 218 19.4 0.50 0.39–0.64
Not having access to Internet gambling at home 25.48 <.0001
 Important 396 54.7 750 66.4 Ref --
 Not important 328 45.3 380 33.6 0.69 0.55–0.87
Parent/Guardian strictness about gambling 46.74 <.0001
 Important 498 68.3 924 82.1 Ref --
 Not important 231 31.7 202 17.9 0.54 0.31–0.69
Warnings from adults in family 54.79 <.0001
 Important 493 67.7 926 82.6 Ref --
 Not important 235 32.3 195 17.4 0.53 0.41–0.68
Warnings from, or listening to, peers 41.63 <.0001
 Important 508 70.2 932 82.9 Ref --
 Not important 216 29.8 192 17.1 0.62 0.48–0.80
Having parents who don’t gamble 56.67 <.0001
 Important 479 65.9 917 81.6 Ref --
 Not important 248 34.1 207 18.4 0.54 0.42–0.70
Learning about the risks of gambling in school 63.50 <.0001
 Important 456 62.6 892 79.5 Ref --
 Not important 272 37.4 230 20.5 0.52 0.41–0.66
Learning about the risks of gambling from parents 54.90 <.0001
 Important 505 69.3 944 83.8 Ref --
 Not important 224 30.7 182 16.2 0.54 0.42–0.70
Learning about the risks of gambling from peers 58.98 <.0001
 Important 476 65.0 909 80.9 Ref --
 Not important 255 35.0 215 19.1 0.55 0.43–0.70
Adults not involving kids in gambling 79.51 <.0001
 Important 496 68.0 957 85.5 Ref --
 Not important 233 32.0 163 14.5 0.45 0.34–0.58
Parent/Guardian not permitting card games (for money) at home 42.99 <.0001
 Important 381 52.3 758 67.4 Ref --
 Not important 348 47.7 366 32.6 0.52 0.42–0.65
Family concern 6.35 .0118
 Yes 115 15.9 131 11.8 Ref --
 No 608 84.1 979 88.2 1.43 1.03–1.97
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Substance use and Internet gambling

Among both GS+ and GS- adolescents, ARPG versus recreational gambling was associated with drug use and Internet gambling (Table 3a). In adjusted logistic regression models, GS+ status did not moderate relationships between ARPG and either substance-use or Internet-gambling measures (data not shown).

Table 3a.

Unadjusted analyses of problem-gambling severity and substance use, Internet gambling and gambling partners.

Variable Gambles on School Ground (GS+) Does Not Gamble on School Ground (GS-)
Recreational Gambling ARPG X2 p Recreational Gambling ARPG X2 p
N % N % N % N %
Substance Use
 Smoking 2.11 .35 4.77 .09
  Never 161 47.3 180 43.0 587 62.6 126 17.7
  Occasionally 103 30.3 128 30.5 230 24.5 67 22.6
  Regularly 76 22.4 111 26.5 121 12.9 37 23.4
 Marijuana 2.80 .09 0.34 .56
  Ever 192 58.0 260 64.0 335 37.4 85 39.5
 Alcohol 2.23 .53 1.21 .75
  Never regular 62 24.2 62 21.0 197 31.9 40 28.5
  Light 57 22.3 69 23.3 184 29.8 48 34.3
  Moderate 92 35.9 100 33.8 170 27.5 38 27.1
  Heavy 45 17.6 65 22.0 66 10.7 14 10.0
  Other drug 5.45 .02 5.42 .02
  Ever 50 19.5 93 27.8 57 7.55 23 13.0
Internet Gambling 91 25.8 196 45.0 30.99 <.0001 81 8.4 41 16.9 15.75 <.0001
Gambling Partners
 Family 183 51.4 233 52.7 .14 .71 365 37.4 128 52.9 19.32 <.0001
 Friends 326 91.2 369 83.5 11.48 .0007 556 57.0 176 72.7 20.1 <.0001
 Other adults 99 27.8 180 40.7 14.46 .0001 142 14.6 66 27.3 22.17 <.0001
 Strangers 27 7.6 115 26.0 45.81 <.0001 18 1.8 15 6.2 13.95 .0002
 Alone 26 7.3 87 19.7 24.86 <.0001 35 3.6 27 11.2 23.01 <.0001
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ARPG = At-Risk/Problematic Gambling

Gambling partners

GS+ status moderated relationships between specific gambling partners and ARPG (Table 3b). Among students reporting GS+, ARPG, relative to recreational gambling, was associated with a decreased odds of gambling with friends (OR=.44; 95%CI [.26–.74]) and increased odds of other adults (OR=1.72; 95%CI=1.24–2.38), strangers (OR=3.61; 95%CI=2.24–5.82), and alone (OR=2.65; 95%CI=1.62–4.36). Among students reporting GS-, ARPG, in comparison with recreational gambling, was associated with increased odds of gambling with family (OR=1.79; 95%CI=1.30–.2.45), friends (OR=2.00; 95%CI=1.41–2.83), other adults (OR=2.31; 95%CI=1.59–3.37), and gambling alone (OR=2.58; 95%CI=1.40–4.75). Interaction odds ratios showed a weaker relationship between ARPG and gambling with friends in the GS+, relative to the GS- groups (OR=0.21; 95%CI=0.11–0.39). Interaction odds ratios also showed a weaker relationship between ARPG and gambling with family in the GS+, relative to the GS- groups (OR=0.60; 95%CI=0.39–0.92). Numerically larger proportions of ARPG adolescents in the GS+ vs. GS- groups reported gambling with friends (83.5% vs. 72.7%), strangers (26.0% vs. 6.2%), other adults (40.7% vs. 27.3%), and alone (19.7% vs. 11.2%), whereas roughly equal proportion of ARPG adolescents in the GS+ and GS- groups reported gambling with family members (52.7% and 52.9% respectively). However, larger proportions of adolescents who gambled recreationally in the GS+ vs. GS- groups reported gambling with family (51.4% vs. 37.4%), friends (91.2% vs. 57.0%), other adults (27% vs. 14.6%), strangers (7.6% vs. 1.8%) and alone (7.3% vs. 3.6%), and these larger proportions in the GS+ recreational-gambling group may have in part driven the interaction effects.

Table 3b.

Multivariate-adjusted analyses of problem-gambling severity and gambling partners stratified by GS status

Gambles on School Ground (GS+) Does Not Gamble on School Ground [GS+ (ARPG VS
Recreational Gambling)]
VS [GS+ (ARPG VS Recreational Gambling)]
ARPG VS Recreational Gambling (GS-) ARPG VS Recreational Gambling
OR 95% CI OR 95% CI Interaction OR 95% CI
Gambling Partners
 Family 1.05 0.77–1.43 1.79 1.30–2.45 0.60 0.39–0.92
 Friends 0.44 0.26–0.74 2.00 1.41–2.83 0.21 0.11–0.39
 Other adults 1.72 1.24–2.38 2.31 1.59–3.37 0.76 0.47–1.24
 Strangers 3.61 2.24–5.82 1.94 0.82–4.60 1.62 0.63–4.17
 Alone 2.65 1.62–4.36 2.58 1.40–4.75 0.92 0.43–1.98
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ARPG = At-Risk/Problematic Gambling; OR= Odds Ratio

Discussion

The present study examined in high-school students: 1) the relationships between GS+ status and academic performance, ARPG and gambling-related attitudes and perceptions; and, 2) the extent to which GS+ moderated relationships between ARPG and gambling partner status. Hypotheses were largely supported. In comparison to GS- students, GS+ students were more likely to report poorer academic performance, ARPG and pathological gambling, and more permissive attitudes towards gambling. GS+ status also moderated the relationship between ARPG and gambling partners, with differences noted with respect to relationships with gambling with peers and family members.

GS+ and Gambling Problems

The almost five-fold higher estimates of pathological gambling amongst GS+ adolescents, in comparison to GS- adolescents (as well as the elevated frequency of ARPG), is noteworthy and suggests that more research is needed to identify the directionality of this relationship. That is, it will be important to understand whether the relationship is such that GS+ promotes gambling problems in youth, versus the reverse (whether problem gambling leads to GS+). Additionally, further work is needed to identify relevant mechanisms and sequelae of this association. In conjunction with the high frequency of GS+ in the sample (40%), the findings suggest the need for improved interventions to limit GS+. Such interventions might include school-based strategies regarding policy, detection, and prevention of school-grounds gambling activities.

GS+ and academic performance

In comparison to GS- students, GS+ students were more likely to report poorer academic performance. These findings support the perspective that attention to student gambling, and particularly adolescents gambling on school grounds, to prevent impaired academic performance among adolescents is needed (Winters, Stinchfield, Botzet, & Anderson, 2002; Yip et al., 2011) and although examinations are needed, this raises the possibility that school-grounds-based (Galan et al., 2012) gambling prevention strategies may warrant consideration with respect to diminishing at-risk or problematic gambling. It is possible that intervening against GS+ may have positive effects on academic performance. However, the opposite might also be true such that helping students to achieve greater academic success may have protective effects against GS+. Longitudinal examinations could clarify the directionality of this relationship and provide additional important temporal information including types and patterns of such gambling.

GS+ and gambling-related attitudes and perceptions

Relative to GS- students, GS+ students were more likely to report more permissive attitudes towards gambling. This extends previous findings from this survey documenting relationships between gambling and perceived parental permissiveness towards gambling related to impulsivity, sensation-seeking, alcohol consumption, and receipt of instant lottery tickets as gifts (Kundu et al., 2013; Leeman et al., 2014; Rahman et al., 2014). Parental permissiveness has been linked to other risk behaviors performed on school grounds. Having parental permission to smoke has previously been associated with higher probability of smoking on school premises (Galan et al., 2012), and our findings suggest similarities with gambling-related permissiveness among the GS+ group. This may suggest that parental monitoring and communication may be influential in regards to gambling perceptions and behaviors among youth, and good communication between adolescents and parents with respect to potential risks associated with gambling may be an important next step in terms of prevention strategies (Rahman et al., 2014). It will be important to examine whether emphasizing the importance of adult awareness of gambling and the risks thereof may help effect change in gambling perceptions among adolescents at risk for problem gambling (Rahman et al., 2014; Turrisi et al., 2013). It is also worth noting that the GS+ group was less likely than the GS- group to report concern about other family members’ gambling behavior, which further suggests tolerance of gambling behaviors among those with GS+ status.

GS+and gambling partners

Among students reporting GS+, ARPG (relative to recreational gambling) was associated with decreased odds of gambling with friends. This was somewhat unexpected given prior work suggesting that problem behaviors among adolescents are strongly associated with peers engaging in the same problem behavior (Delfabbro & Thrupp, 2003). This finding may reflect the frequent gambling with friends observed in the recreational-gambling group in the GS+ group. Among GS+ students, ARPG was associated with increased odds of gambling with other adults, gambling with strangers, and gambling alone. Thus, the GS+ ARPG group may be exhibiting risky gambling with potentially non-traditional gambling partners.

Examination of interactions among these variables revealed that GS+ status moderated the relationship between ARPG and gambling partners, with differences specifically noted for peers and family members. Findings indicated a stronger association between ARPG and gambling with both friends and family in the GS- relative to the GS+ group, and these differences appear to be in part driven by how GS+ relates to ARPG in comparison to recreational gambling. While no moderating effect emerged between GS status and ARPG on the association between gambling with strangers, potential mediators or moderators not examined in the present study which could account for this lack of effect might include excessive use of mobile devices for Internet-based gambling or other purposes (Martinotti et al., 2011; Villella et al., 2011), although this possibility is purely speculative. Additional examinations should explore how gambling via smartphone or other forms of digital technology at school may relate to gambling on school grounds.

Present findings demonstrate that among both the ARPG and recreational-gambling groups, higher proportions of youth in the GS+ group, relative to the GS- one, reported gambling with varying partners including strangers. Although not investigated in the present survey, future studies could investigate which strangers have been gambling with adolescents, and in what context this may have taken place (e.g., meeting strangers on school grounds or gambling with online strangers via mobile devices while on school grounds). A better understanding of the relationships between gambling with strangers, GS+, and ARPG among adolescents is needed, as this would allow for more appropriately designed and tailored intervention strategies for youth.

Implications for school policies, education and interventions

The present research represents one of the first examinations of GS+ in conjunction with gambling-related perceptions and attitudes, and gambling behaviors among adolescents. Analyses were conducted on data from a large and ecologically valid sample of high-school students in Connecticut, and these findings can inform more efficient treatment and prevention programs in efforts to mitigate problem gambling among high-school students. While most efforts target problem gambling among adults, there is a paucity of research examining school grounds gambling. Risky behaviors including substance misuse can begin during adolescence and have been linked with high-school gambling (Lee et al., 2014; Patterson, Myers, & Gallant, 1988), As substance-using ARPG adolescents may be more likely to seek treatment when it is available (Duhig, Maciejewski, Desai, Krishnan-Sarin, & Potenza, 2007), early identification is important.

Earlier identification may be facilitated through teachers and other school officials highlighting, in nonjudgmental ways, the availability of treatment programs to students (Byrne, Baron, Larsson, & Melin, 1996). The use of teacher or administrator reports (Moore, Roberts, & Tudor-Smith, 2001; Wakefield et al., 2000) and encouraging the establishment of school policies related to banning gambling on school premises and enforcing such policies may facilitate reductions of gambling on school grounds. Further, research suggests that perceptions of more strictly enforced restrictions have been effective deterrents with respect to smoking (Adams, Jason, Pokorny, & Hunt, 2009; Leatherdale & Manske, 2005), and this indicates potential utility in expanding jurisdiction covered by school gambling restrictions. It will be of continued importance to increase awareness of adverse health outcomes and risks associated with GS+ among adolescents, teachers, families, educators, pediatricians, and other professionals.

Of particular concern is the growing prevalence of internet gambling (King & Barak, 1999), the spread of which may be facilitated by increasing use of smartphones and other mobile devices (Griffiths & Parke, 2010; King, Delfabbro, & Griffiths, 2010). As gambling via mobile devices likely consititutes some of the reported school-ground and off-grounds gambling (e.g., gambling via social media platforms; Griffiths & Parke, 2010), it will be important to understand to what extent GS+ status is enabled by digital devices. In support of this perspective, findings from the present study suggest that among GS+ students, those meeting ARPG criteria were more than three times more likely to report gambling with strangers relative to students who gambled recreationally. It is possible that youth may be using the Internet at school (e.g., via smart phones or school computers) to gamble with strangers, and this possibility, while speculative, warrants direct examination. In general, further work is needed to better understand the specific nature, modifiable precursors, and underlying mechanisms of GS+ among adolescents in order to best understand how to intervene.

Limitations

Possible limitations relate to the sample, as this sample is not random; however, demographics were consistent with those reported in the 2000 Census of Connecticut residents between the ages of 14–18 (Bureau, 2000; Schepis et al., 2008). Moreover, these data may not reflect current prevalence rates, and further work is needed to better understand forms of gambling that are growing in popularity, including gambling via social media. Possible limitations also relate to the survey metholodogy (self-report with possible responder biases and inaccurate recall). Respondents may have underreported or overreported engagement in certain (e.g., illegal) behaviors for reasons of shame or bravado, respectively. The cross-sectional design of the present study mitigates abilities to make inferences related to causality among variables; additional work is needed to determine temporal relationships between GS+ and measures examined.

Conclusion

Efforts to mitigate harm among students engaging in GS+ and better understand potential points of intervention are warranted. The present study examined GS+ and GS-, and determined whether differences exist between ARPG and recreational-gambling groups on a range of demographic and gambling-related, perceptions, attitudes, and behaviors. Findings indicated that in comparison to GS- students, GS+ students were more likely to report poorer academic performance, ARPG, and more permissive attitudes towards gambling. GS+ status also moderated the relationship between ARPG and gambling partners, with differences noted with respect to relationships with gambling with peers and family members. The findings suggest that it is important to school-based efforts to increase the awareness of GS+ among adolescents such that teachers, students, families, educators, pediatricians, and other professionals may approapriately intervene.

Acknowledgments

This project was supported by National Institute of Health grants R01 DA019039, RL1 AA017539, UL1 DE19586, 5T32MH014235, and K12-DA-000167, the Connecticut Mental Health Center, the Connecticut State Department of Mental Health and Addiction Services, and a Center of Excellence in Gambling Research Award from the National Center for Responsible Gaming.

Footnotes

Conflict of Interest

The authors report no conflicts of interest with respect to the content of this manuscript.

Contributors

Dawn Foster and Marc Potenza developed initial drafts of the manuscript. Rani Hoff and Corey Pilver supported analyses. Yvonne Yau, Marvin Steinberg, Jeremy Wampler, and Suchitra Krishnan-Sarin supported manuscript refinement.

Financial Disclosures

Regarding financial disclosure, Dr. Potenza has: consulted for and advised Boehringer Ingelheim, Lundbeck, Ironwood, Shire and INSYS; has consulted for and had financial interests in Somaxon; received research support from the National Institutes of Health, Veteran’s Administration, Mohegan Sun Casino, the National Center for Responsible Gaming and its affiliated Institute for Research on Gambling Disorders, and Forest Laboratories, Ortho-McNeil, Oy-Control/Biotie, Glaxo-SmithKline, Pfizer and Psyadon pharmaceuticals; 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 disorders; provides 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; has guest-edited 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.

References

  1. Adams ML, Jason LA, Pokorny S, Hunt Y. The relationship between school policies and youth tobacco use. J Sch Health. 2009;79(1):17–23. doi: 10.1111/j.1746-1561.2008.00369.x. quiz 41–13. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Agaku IT, Ayo-Yusuf OA, Vardavas CI, Connolly G. Predictors and patterns of cigarette and smokeless tobacco use among adolescents in 32 countries, 2007–2011. J Adolesc Health. 2014;54(1):47–53. doi: 10.1016/j.jadohealth.2013.07.037. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Barnes GM, Welte JW, Hoffman JH, Tidwell MC. Gambling, alcohol, and other substance use among youth in the United States. J Stud Alcohol Drugs. 2009;70(1):134–142. doi: 10.15288/jsad.2009.70.134. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Bureau USC. Census 2000 Data for the State of Connecticut. 2000 Retrieved June 15, 2011, from http://www.census.gov/census2000/states/ct.html.
  5. Burge AN, Pietrzak RH, Petry NM. Pre/early adolescent onset of gambling and psychosocial problems in treatment-seeking pathological gamblers. J Gambl Stud. 2006;22(3):263–274. doi: 10.1007/s10899-006-9015-7. [DOI] [PubMed] [Google Scholar]
  6. Byrne BM, Baron P, Larsson B, Melin L. Measuring depression for Swedish nonclinical adolescents: factorial validity and equivalence of the Beck Depression Inventory across gender. Scand J Psychol. 1996;37(1):37–45. doi: 10.1111/j.1467-9450.1996.tb00637.x. [DOI] [PubMed] [Google Scholar]
  7. Cairney J, Lawrance KA. Smoking on campus. An examination of smoking behaviours among post-secondary students in Canada. Can J Public Health. 2002;93(4):313–316. doi: 10.1007/BF03405024. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Cavallo DA, Smith AE, Schepis TS, Desai R, Potenza MN, Krishnan-Sarin S. Smoking expectancies, weight concerns, and dietary behaviors in adolescence. Vol. 126. US: American Academy of Pediatrics; 2010. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Cavallo DA, Smith AE, Schepis TS, Desai R, Potenza MN, Krishnan-Sarin S. Smoking expectancies, weight concerns, and dietary behaviors in adolescence. Pediatrics. 2010;126(1):e66–72. doi: 10.1542/peds.2009-2381. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Delfabbro P, Thrupp L. The social determinants of youth gambling in South Australian adolescents. J Adolesc. 2003;26(3):313–330. doi: 10.1016/s0140-1971(03)00013-7. [DOI] [PubMed] [Google Scholar]
  11. Duhig AM, Maciejewski PK, Desai RA, Krishnan-Sarin S, Potenza MN. Characteristics of adolescent past-year gamblers and non-gamblers in relation to alcohol drinking. Addict Behav. 2007;32(1):80–89. doi: 10.1016/j.addbeh.2006.03.021. [DOI] [PubMed] [Google Scholar]
  12. Eisenmann JC, Bartee RT, Wang MQ. Physical activity, TV viewing, and weight in U.S. youth: 1999 Youth Risk Behavior Survey. Obes Res. 2002;10(5):379–385. doi: 10.1038/oby.2002.52. [DOI] [PubMed] [Google Scholar]
  13. Elliott JC, Carey KB. Pros and cons: prospective predictors of marijuana use on a college campus. Psychol Addict Behav. 2013;27(1):230–235. doi: 10.1037/a0029835. [DOI] [PubMed] [Google Scholar]
  14. Emory KT, Messer K, Vera L, Ojeda N, Elder JP, Usita P, Pierce JP. Receptivity to cigarette and tobacco control messages and adolescent smoking initiation. Tob Control. 2014 doi: 10.1136/tobaccocontrol-2013-051187. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Foster DW, Neighbors C, Rodriguez LM, Lazorwitz B, Gonzales R. Self-identification as a moderator of the relationship between gambling-related perceived norms and gambling behavior. J Gambl Stud. 2014;30(1):125–140. doi: 10.1007/s10899-012-9346-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Galan I, Diez-Ganan L, Mata N, Gandarillas A, Cantero JL, Durban M. Individual and contextual factors associated to smoking on school premises. Nicotine Tob Res. 2012;14(4):495–500. doi: 10.1093/ntr/ntr174. [DOI] [PubMed] [Google Scholar]
  17. Gori M, Potente R, Pitino A, Scalese M, Bastiani L, Molinaro S. Relationship Between Gambling Severity and Attitudes in Adolescents: Findings from a Population-Based Study. J Gambl Stud. 2014 doi: 10.1007/s10899-014-9481-2. [DOI] [PubMed] [Google Scholar]
  18. Griffiths MD, Parke J. Adolescent gambling on the internet: a review. Int J Adolesc Med Health. 2010;22(1):59–75. [PubMed] [Google Scholar]
  19. Hammond CJ, Pilver CE, Rugle L, Steinberg MA, Mayes LC, Malison RT, Potenza MN. An exploratory examination of marijuana use, problem-gambling severity, and health correlates among adolescents. J Behav Addict. 2014;3(2):90–101. doi: 10.1556/JBA.3.2014.009. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Hardoon KK, Gupta R, Derevensky JL. Psychosocial variables associated with adolescent gambling. Psychol Addict Behav. 2004;18(2):170–179. doi: 10.1037/0893-164X.18.2.170. [DOI] [PubMed] [Google Scholar]
  21. Hennessy EA, Tanner-Smith EE. Effectiveness of Brief School-Based Interventions for Adolescents: A Meta-analysis of Alcohol Use Prevention Programs. Prev Sci. 2014 doi: 10.1007/s11121-014-0512-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. King D, Delfabbro P, Griffiths M. The convergence of gambling and digital media: implications for gambling in young people. J Gambl Stud. 2010;26(2):175–187. doi: 10.1007/s10899-009-9153-9. [DOI] [PubMed] [Google Scholar]
  23. King SA, Barak A. Compulsive internet gambling: a new form of an old clinical pathology. Cyberpsychol Behav. 1999;2(5):441–456. doi: 10.1089/cpb.1999.2.441. [DOI] [PubMed] [Google Scholar]
  24. Kong G, Tsai J, Pilver CE, Tan HS, Hoff RA, Cavallo DA, Potenza MN. Differences in gambling problem severity and gambling and health/functioning characteristics among Asian-American and Caucasian high-school students. Psychiatry Res. 2013;210(3):1071–1078. doi: 10.1016/j.psychres.2013.10.005. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Kundu PV, Pilver CE, Desai RA, Steinberg MA, Rugle L, Krishnan-Sarin S, Potenza MN. Gambling-related attitudes and behaviors in adolescents having received instant (scratch) lottery tickets as gifts. J Adolesc Health. 2013;52(4):456–464. doi: 10.1016/j.jadohealth.2012.07.013. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Langhinrichsen-Rohling J, Rohde P, Seeley JR, Rohling ML. Individual, family, and peer correlates of adolescent gambling. J Gambl Stud. 2004;20(1):23–46. doi: 10.1023/B:JOGS.0000016702.69068.53. [DOI] [PubMed] [Google Scholar]
  27. Leatherdale ST, Manske S. The relationship between student smoking in the school environment and smoking onset in elementary school students. Cancer Epidemiol Biomarkers Prev. 2005;14(7):1762–1765. doi: 10.1158/1055-9965.EPI-05-0065. [DOI] [PubMed] [Google Scholar]
  28. Lee GP, Martins SS, Pas ET, Bradshaw CP. Examining potential school contextual influences on gambling among high school youth. Am J Addict. 2014;23(5):510–517. doi: 10.1111/j.1521-0391.2014.12142.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Leeman RF, Patock-Peckham JA, Hoff RA, Krishnan-Sarin S, Steinberg MA, Rugle LJ, Potenza MN. Perceived parental permissiveness toward gambling and risky behaviors in adolescents. J Behav Addict. 2014;3(2):115–123. doi: 10.1556/JBA.3.2014.012. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Lloyd J, Doll H, Hawton K, Dutton WH, Geddes JR, Goodwin GM, Rogers RD. How psychological symptoms relate to different motivations for gambling: an online study of internet gamblers. Biol Psychiatry. 2010;68(8):733–740. doi: 10.1016/j.biopsych.2010.03.038. [DOI] [PubMed] [Google Scholar]
  31. Manthey JL, Aidoo AY, Ward KY. Campus drinking: an epidemiological model. J Biol Dyn. 2008;2(3):346–356. doi: 10.1080/17513750801911169. [DOI] [PubMed] [Google Scholar]
  32. Martinotti G, Villella C, Di Thiene D, Di Nicola M, Bria P, Conte G, La Torre G. Problematic mobile phone use in adolescence: A cross-sectional study. Journal of Public Health. 2011;19(6) doi: 10.1007/s10389-011-0422-6. [DOI] [Google Scholar]
  33. Moore L, Roberts C, Tudor-Smith C. School smoking policies and smoking prevalence among adolescents: multilevel analysis of cross-sectional data from Wales. Tob Control. 2001;10(2):117–123. doi: 10.1136/tc.10.2.117. [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Patterson EW, Myers G, Gallant DM. Patterns of substance use on a college campus: a 14-year comparison study. Am J Drug Alcohol Abuse. 1988;14(2):237–246. doi: 10.3109/00952999809001549. [DOI] [PubMed] [Google Scholar]
  35. Potenza MN, Wareham JD, Steinberg MA, Rugle L, Cavallo DA, Krishnan-Sarin S, Desai RA. Correlates of at-risk/problem internet gambling in adolescents. J Am Acad Child Adolesc Psychiatry. 2011;50(2):150–159. e153. doi: 10.1016/j.jaac.2010.11.006. [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Rahman AS, Balodis IM, Pilver CE, Leeman RF, Hoff RA, Steinberg MA, Potenza MN. Adolescent Alcohol-Drinking Frequency and Problem-Gambling Severity: Adolescent Perceptions Regarding Problem-Gambling Prevention and Parental/Adult Behaviors and Attitudes. Subst Abus. 2014 doi: 10.1080/08897077.2014.951754. [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Schepis TS, Desai RA, Smith AE, Cavallo DA, Liss TB, McFetridge A, Krishnan-Sarin S. Impulsive sensation seeking, parental history of alcohol problems, and current alcohol and tobacco use in adolescents. J Addict Med. 2008;2(4):185–193. doi: 10.1097/adm.0b013e31818d8916. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Shaffer HJ, Forman DP, Scanlan KM, Smith F. Awareness of gambling-related problems, policies and educational programs among high school and college administrators. J Gambl Stud. 2000;16(1):93–101. doi: 10.1023/a:1009435518147. [DOI] [PubMed] [Google Scholar]
  39. Shaffer HJ, Hall MN, Vander Bilt J. Estimating the prevalence of disordered gambling behavior in the United States and Canada: a research synthesis. Am J Public Health. 1999;89(9):1369–1376. doi: 10.2105/ajph.89.9.1369. [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Shaffer HJ, Labrie R, Scanlan KM, Cummings TN. Pathological gambling among adolescents: Massachusetts Gambling Screen (MAGS) J Gambl Stud. 1994;10(4):339–362. doi: 10.1007/BF02104901. [DOI] [PubMed] [Google Scholar]
  41. Shead NW, Derevensky JL, Gupta R. Risk and protective factors associated with youth problem gambling. Int J Adolesc Med Health. 2010;22(1):39–58. [PubMed] [Google Scholar]
  42. Slavin M, Pilver CE, Hoff RA, Krishnan-Sarin S, Steinberg MA, Rugle L, Potenza MN. Serious Physical Fighting and Gambling-Related Attitudes and Behaviors in Adolescents. J Behav Addict. 2013;2(3):167. doi: 10.1556/JBA.2.2013.009. [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Turrisi R, Mallett KA, Cleveland MJ, Varvil-Weld L, Abar C, Scaglione N, Hultgren B. Evaluation of timing and dosage of a parent-based intervention to minimize college students' alcohol consumption. J Stud Alcohol Drugs. 2013;74(1):30–40. doi: 10.15288/jsad.2013.74.30. [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Villella C, Martinotti G, Di Nicola M, Cassano M, La Torre G, Gliubizzi MD, Conte G. Behavioural addictions in adolescents and young adults: results from a prevalence study. J Gambl Stud. 2011;27(2):203–214. doi: 10.1007/s10899-010-9206-0. [DOI] [PubMed] [Google Scholar]
  45. Volberg RA, Gupta R, Griffiths MD, Olason DT, Delfabbro P. An international perspective on youth gambling prevalence studies. Int J Adolesc Med Health. 2010;22(1):3–38. [PubMed] [Google Scholar]
  46. Wakefield MA, Chaloupka FJ, Kaufman NJ, Orleans CT, Barker DC, Ruel EE. Effect of restrictions on smoking at home, at school, and in public places on teenage smoking: cross sectional study. BMJ. 2000;321(7257):333–337. doi: 10.1136/bmj.321.7257.333. [DOI] [PMC free article] [PubMed] [Google Scholar]
  47. Walters ST, Bennett ME, Noto JV. Drinking on campus. What Do we know about reducing alcohol use among college students? J Subst Abuse Treat. 2000;19(3):223–228. doi: 10.1016/s0740-5472(00)00101-x. [DOI] [PubMed] [Google Scholar]
  48. Winters KC, Stinchfield RD, Botzet A, Anderson N. A prospective study of youth gambling behaviors. Psychol Addict Behav. 2002;16(1):3–9. doi: 10.1037//0893-164x.16.1.3. [DOI] [PubMed] [Google Scholar]
  49. Yau YHC, Pilver CE, Steinberg MA, Rugle LJ, Hoff RA, Krishnan-Sarin S, Potenza MN. Relationships between problematic Internet use and problem-gambling severity: Findings from a high-school survey. Vol. 39. Netherlands: Elsevier Science; 2014. [DOI] [PMC free article] [PubMed] [Google Scholar]
  50. Yip SW, Desai RA, Steinberg MA, Rugle L, Cavallo DA, Krishnan-Sarin S, Potenza MN. Health/functioning characteristics, gambling behaviors, and gambling-related motivations in adolescents stratified by gambling problem severity: findings from a high school survey. Am J Addict. 2011;20(6):495–508. doi: 10.1111/j.1521-0391.2011.00180.x. [DOI] [PMC free article] [PubMed] [Google Scholar]

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