Relationships Between Sport Participation,Problem Alcohol Use,and Violence

Abstract

There is a growing body of evidence suggesting a link between sport participation and violent behavior outside of the sporting context. However, there have been few studies that have investigated the basis of this relationship. The current study examined longitudinal relationships between sport participation, problem alcohol use, and various violent behaviors, and whether sport participation moderates relationships between problem alcohol use and violence. The sample comprised 2,262 young adults (55% female, age range at Time 1 = 17-24 years) from Victoria, Australia, surveyed in 2010 and 2012. When controlling for common risk factors, substance use, and past violence, sport participation was not associated with any violent behaviors 2 years later. However, sport participation moderated the relationship between problem alcohol use and fighting, whereby problem alcohol use was associated with engaging in fights 2 years later for sport participants, but not for nonparticipants. These findings suggest that it is not sport participation per se that influences later violence but the drinking norms or culture embedded within certain sporting contexts. Prevention approaches that address the drinking culture and social approval of excessive alcohol consumption within sporting contexts may reduce the incidence of violent behavior in the community.

Keywords

sport alcohol use problems violence young adult

Media reports of high profile athletes’ involvement in aggressive and violent incidents have focused attention on the relationship between sport participation and violence. While many of these violent or aggressive incidents take place on the field in the context of sports competition, there are also reports of violence against members of the community, and often with respect to women in intimate and nonintimate situations. Despite this anecdotal evidence of a link between sport involvement and community violence, there have been relatively few empirical studies that have been able to appropriately examine this relationship (Kimble, Russo, Bergman, & Galindo, 2010).

Of the studies that do exist, many have found evidence to suggest that involvement in sport may be associated with violence and aggression outside of the sporting context. Participation in sport has been shown to be associated with family violence (Bloom & Smith, 1996), laboratory measures of aggression (D. B. Huang, Cherek, & Lane, 1999), sexual violence/aggression (Frinter & Rubinson, 1993; Koss & Gaines, 1993; Murnen & Kohlman, 2007), violent delinquency (Segrave, Moreau, & Hastad, 1985), and physical and/or verbal aggression/violence (Burton & Marshall, 2005; Endresen & Oleweus, 2005; Linville & Huebner, 2005; Nixon, 1997; O’Brien et al., 2012). Gender (Linville & Huebner, 2005; Miller, Melnick, Farrell, Sabo, & Barnes, 2006; Nixon, 1997; O’Brien et al., 2012), type of sport (e.g., contact or noncontact sport; Nixon, 1997), level of competitiveness (Bloom & Smith, 1996), and whether or not an individual perceives himself or herself as an athlete or “jock” (Miller et al., 2006) may also influence these relationships. It should be noted that not all studies have observed relationships between sport participation and violent behavior off-field (Kimble et al., 2010). For example, among college men, participation in sport (membership on a competitive sports team) was not found to be predictive of perpetration of verbal, physical, or sexual violence 3 months later when prior violent behavior was taken into account (Gidycz, Warkentin, & Orchowski, 2007).

There are a number of theories that help explain potential relationships between sport participation and violence. Social learning theory suggests that aggressive behaviors are learned through the confrontational nature of some sports (e.g., tackling, use of physical force, fighting skills in sports such as boxing or wrestling; Endresen & Oleweus, 2005). Furthermore, enactive learning and contact with aggressive role models during training and competition may enhance aggressive behaviors in the sporting context and the normalization or social approval of such behaviors (Endresen & Oleweus, 2005). Cultural spillover theory suggests that socially approved forms of aggression or violence can then have a carryover effect to more forbidden forms of aggression or violence, such as outside of the sporting context (Bloom & Smith, 1996).

Participation in sport has also been consistently linked with alcohol use, with many studies showing that members of sporting clubs (Poortinga, 2007) and athletes (Gmel, Kuendig, & Daeppen, 2009; Leichliter, Meilman, Presley, & Cashin, 1998; O’Brien et al., 2012; O’Brien, Kolt, Webber, & Hunter, 2010) report greater alcohol consumption and more harm associated with alcohol consumption than nonsports people. For example, a large study of college students in the United States found that athletes reported more heavy episodic drinking, heavier alcohol use, and a greater level of drinking-related harms than nonathletes (Nelson & Wechsler, 2001). Furthermore, level of involvement in sport may influence the relationship between sport participation and alcohol use, with elite sports people reporting higher rates of hazardous drinking than both nonelite sports people and nonsports people (O’Brien, Ali, Cotter, O’Shea, & Stannard, 2007; O’Brien, Blackie, & Hunter, 2005; Sonderlund et al., 2014).

There is also a well-established link between alcohol use and violent behavior. Experimental studies have shown that alcohol has an indirect causal influence on violent behavior, by way of cognitive, emotional, or physiological changes caused by alcohol consumption, which increase the likelihood of aggressive responses (for a review, see Exum, 2006). Longitudinally, alcohol use has also been found to predict later violent behavior (outside of the period of intoxication) in a number of studies (Dembo et al., 1993; Ellickson, Tucker, & Klein, 2003; Newcomb & McGee, 1989; Scholes-Balog, Hemphill, Kremer, & Toumbourou, 2013), while other studies have suggested bidirectional or reciprocal longitudinal relationships between alcohol use and violence (Scholes-Balog et al., 2013; White, Loeber, Stouthamer-Loeber, & Farrington, 1999; Windle, 1990; Zue, Zimmerman, & Cunningham, 2009). Longitudinal studies also support an indirect causal relationship between alcohol use and later violent behavior, with factors such as affiliation with antisocial and substance using peers appearing to explain these relationships (e.g., Scholes-Balog et al., 2013).

While the bulk of the literature has examined violence in relation to sports participation and alcohol consumption separately, there is a small body of literature that has attempted to evaluate the relationship among all three factors (for a review, see Sonderlund et al., 2014). A qualitative study among athletes found that athletes often attribute alcohol use as the cause of their violent behavior outside of the sporting context (Pappas, McKenry, & Skilken Catlett, 2004). Similarly, off-field alcohol-related aggression and antisocial behavior was found to be common among professional Australian Football League players (Dietze, Fitzgerald, & Jenkinson, 2008). In this study, 26% of players surveyed reported getting involved in a fight (either verbal or physical) while drinking (Dietze et al., 2008). Likewise, a study of Australian university students found that university sport participants were more likely than nonsport participants to have displayed aggressive behavior (insulted or assaulted someone) when intoxicated in the past year (O’Brien et al., 2012). The university sport participant sample included participants in both individual (e.g., running, squash) and team sports (e.g., football, cricket). In this study, gender also played a role, with alcohol-related violence and aggression more likely among male university sport participants than among female sport participants (O’Brien et al., 2012). Given the mounting evidence suggesting a higher rate of alcohol consumption and violence among athletes, relative to nonathletes, Sonderlund et al. (2014) suggested that sport participation may have a moderating effect on the positive relationship between alcohol and violence. However, this suggestion has yet to be empirically tested. Nonetheless, the context in which drinking takes place (and the associated dynamics of such context) has been shown to play a role in alcohol-related violence. For instance, public drinking (as compared with private drinking) is a strong predictor of violence (Rossow, 1996; Tomsen, 1997). Similarly, drinking among sporting spectators is thought to play a role in spectator aggression and violence at sporting matches (Bormann & Stone, 2001; Moore, Shepherd, Eden, & Sivarajasingam, 2007), with the social dynamics of the spectator crowd thought to also drive this relationship (Roberts & Benjamin, 2000).

It should be noted that the bulk of the literature examining alcohol use, sport participation, and violence is cross-sectional in nature. One longitudinal study found that neither alcohol use nor sport participation predicted violence or aggression, when controlling for past history of violence and aggression (Gidycz et al., 2007). Another longitudinal study did not find sport participation itself to be predictive of violence, but rather “jock” identity (those who subjectively perceive themselves, and are perceived by others, as athletes or “jocks”) was associated with a higher frequency of violence (Miller et al., 2006). Furthermore, “jock” identity moderated the relationship between alcohol use and violence, whereby alcohol use predicted violence only among nonjocks (Miller et al., 2006).

There are a number of limitations of the published literature to date. First, the literature is dominated by studies of North American college samples (Sonderlund et al., 2014). Factors such as drinking cultures, sports team dynamics and subcultures, and social norms may vary between countries. For example, in Australia there is no named subculture synonymous with “jock,” though such a subculture may exist without name, or simply less pejoratively termed “sporty” or “athlete.” Nonetheless, literature investigating “jock” identity is not easily comparable in an Australian setting. Similarly, in countries where sport participation is not as valued or esteemed as in the United States, the customs associated with these sports may be less likely to influence participants’ behavior (Sonderlund et al., 2014). Furthermore, as mentioned previously, the vast majority of published studies investigating sport participation, alcohol use, and violence are of cross-sectional design and therefore are unable to assess temporal ordering or control for prior violent behavior when assessing relationships between sport participation and violence. In addition, most studies fail to control for other factors that may explain or account for any observed relationships between sport participation, alcohol use, and violence, such as use of illicit substances and affiliation with deviant peers (Herrenkohl et al., 2007; McMorris, Catalano, Kim, Toumbourou, & Hemphill, 2011; Scholes-Balog et al., 2013).

Given the lack of research directed specifically at understanding the relationships between sport participation, alcohol use, and violence, together with the limitations outlined above, the present study intended to investigate longitudinal relationships between sport participation, problem alcohol use, and violence among a community-based Australian sample. Specifically, this study examines relationships with four violent behaviors: physical intimate partner violence (IPV), emotional IPV, fighting, and assault. It was hypothesized that (a) both alcohol use problems and frequency of sport participation will predict violent behavior 2 years later; (b) as suggested by Sonderlund et al. (2014), sport participation will moderate the relationship between alcohol use problems and violence; and (c) gender will moderate the relationship between alcohol use, sport participation, and violence.

Method

Participants

Young adults from Victoria, Australia, who were involved in the International Youth Development Study (IYDS) comprised the sample for this study. In 2002, 3,948 Victorian students and their parents were approached to take part in this study. Of these, 2,927 parents provided informed consent (74%). Among those students who had parental informed consent, 2,884 (99%) were recruited into the IYDS and completed the survey. Original sampling for the IYDS has been described in detail elsewhere (McMorris, Hemphill, Toumbourou, Catalano, & Patton, 2007) and was designed to yield a state-representative sample of students in Grades 5, 7, and 9 (equivalent to average ages 11, 13, and 15 years). Briefly, the IYDS used a two-stage cluster sampling approach: (a) random selection of public and private schools in Victoria, Australia, stratified according to geographic location, using a probability proportionate to grade-level size sample procedure and (b) random selection of one class at each target grade level (Grades 5, 7, and 9 in 2002) within each school. Longitudinal surveying for the IYDS has occurred between the years 2002 and 2012. The sample for the current study comprised 2,262 (1,260 female, 1,000 male) young adults who were surveyed in both 2010 and 2012 as part of the IYDS longitudinal study and had data available for the measures of violence (this constituted 77% of the original sample who had entered the study in 2002). The current study utilizes these two time points as only questions related to the focus of this article were asked during these surveys. In 2010 (referred to as T1), participants ranged in age from 17 to 24 years of age (M = 21.00, SD = 1.67). In 2012 (referred to as T2), participants ranged in age from 19 to 26 years of age (M = 23.02, SD = 1.66).

Procedure

Ethics approval was obtained from The University of Melbourne Human Ethics in Research Committee. Participants were contacted by mail, email, and/or phone and asked to complete the survey online after providing informed consent. Survey completion took approximately 60 min. After completion of the survey, participants received a small thank you gift (gift voucher).

Measures

Survey items were drawn from a modified version of the Communities That Care youth survey (Glaser, Lee Van Horn, Arthur, Hawkins, & Catalano, 2005; Hemphill et al., 2011) that was adapted for use in young adults.

Sport participation

Participation in sport was assessed at T1 with a question asking, “How many times in the past 12 months have you participated in organized sporting activities (organized by a club, association, or other type of organization)?” This item was scored on an 8-point scale from never (1) to 40+ times (8). As this variable was severely skewed, and could not be rectified with transformation, it was dichotomized for analysis: sport participant (1) was defined as having engaged in sport at least once in the past 12 months, sport nonparticipant (0) was defined as not having engaged in sport at all in the past 12 months.

Alcohol use problems

The Alcohol Use Disorders Identification Test (AUDIT; Babor, de la Fuente, Saunders, & Grant, 1992) was used to measure alcohol use problems at T1. The AUDIT consists of 10 items, each scored on a 5-point scale. Responses to each item are summed to obtain an overall score that ranges between 0 and 40. Higher scores are indicative of greater severity of alcohol-related problems, with scores more than 8 indicating a strong likelihood of harmful alcohol consumption (Babor et al., 1992). The AUDIT has been shown to be valid and reliable among college samples (e.g., Fleming, Barry, & Macdonald, 1991).

Fighting

Engaging in fights was assessed at both T1 and T2. At T1, the item asked, “Have you ever gotten into physical fights with other people?” and the response options were “no,” “yes, but not in the past 12 months,” “yes, once in the past 12 months,” and “yes, more than once in the past 12 months.” At T2, the item asked, “How many times in the past year (12 months) have you got into physical fights with other people?” and the response options ranged from “never” to “10 or more times.” Given the different response options at each time point, for both T1 and T2, these items were dichotomized; a score of 1 indicated that the participant had engaged in fights at least once in the past 12 months, whereas a score of 0 indicated that the participant did not engage in fighting in the past 12 months.

Assault

Perpetration of assault was assessed at both T1 and T2. At T1, the item asked, “Have you ever beat up someone so badly that they probably needed a doctor?” and had the same response options as the T1 fighting item. At T2, the item asked “How many times in the past year (12 months) have you beat up someone so badly that they probably needed to see a doctor?” and had the same response options as the T2 fighting item. As above, at T1 and T2 these items were dichotomized; a score of 1 indicated that the participant had perpetrated assault at least once in the past 12 months, whereas a score of 0 indicated that the participant had not perpetrated assault in the past 12 months.

IPV

Perpetration of IPV in the past 12 months was assessed at both T1 and T2 with a scale containing five items, each assessing perpetration of different types of behaviors: (a) “I pushed, grabbed, slapped, shoved my partner, or threw something at my partner that could hurt”; (b) “I threatened to end our relationship or leave”; (c) “I threatened to hit or throw something at my partner”; (d) “My partner had a physical injury, sprain, bruise, or small cut because of a fight with me”; and (e) “I insulted, swore, or yelled at my partner.” The IPV questions were only asked of participants who indicated they had been/were currently in a relationship in the past 12 months (n = 1,545 at T1 and n = 1,567 at T2). These items were drawn from the revised Conflict Tactics Scale (Straus, Hamby, Boney-McCoy, & Sugarman, 1996), and in some cases, were modified for the purpose of this study. The frequency of each behavior was scored with response options “this has never happened to me” (0), “not in the past year, but it did happen before” (1), “once in the past year” (2), “twice in the past year” (3), “3-5 times in the past year” (4), “6-10 times in the past year” (5), “11-20 times in the past year” (6) and “more than 20 times in the past year” (7). Two measures of IPV were derived from these items: physical IPV (Items a, c, and d) and emotional IPV (Items b and e). To be consistent with the other measures of violence, these measures were dichotomized; a score of 1 indicated that the participant had perpetrated at least one IPV behavior at least once in the past 12 months, whereas a score of 0 indicated that the participant had not perpetrated IPV in the past 12 months.

Common risk factors

A range of risk factors common to both alcohol use and violence were measured at T1 and controlled for in the analyses. Antisocial peers was assessed with a scale containing seven items asking about the number of peers that have engaged in certain antisocial behaviors in the past 12 months (e.g., “In the past year, how many of your best friends have stolen something worth more than $50AUD?”). Each item was scored on a 5-point scale, ranging from none of my friends (0) to 4 of my friends (4). Peer drug use was assessed with a scale containing seven items asking about the number of friends who had used certain types of drugs in the past 12 months (e.g., “In the past year, how many of your best friends have gotten drunk?”). This item was scored on the same rating scale as above. Finally, peer attachment was assessed with two items (e.g., “Think about your four best friends (the friends you feel closest to), in the past year, how many of your best friends have you shared your thoughts and feelings with?”). These items were rated on a 5-point scale from none of my friends (1) to 4 of my friends (5). For each of these scales, scale scores were obtained by taking the mean of the item responses.

In addition, use of other substances were included as covariates in the analyses. Cigarette use was assessed with the item “Have you smoked cigarettes in the past year?” This item was scored on a 5-point scale from never (1) to almost every day or every day (5). Cannabis use was assessed with the item “In the past year, on how many occasions, if any, have you used marijuana (pot, weed, grass)?” This item was scored on an 8-point scale ranging from never (1) to 40+ times (8). Finally, use of other illicit substances was assessed with eight items asking about the frequency of use of different types of illicit substances (lysergic acid diethylamide [LSD], cocaine, inhalants, stimulants, ecstasy, heroin, other illicit drugs, over the counter drugs for recreational/nonmedical purposes). Each item assessing use of each substance was rated on an 8-point scale ranging from never (1) to 40+ times (8). A composite measure of frequency of other illicit substance use was computed by taking the mean of the eight items.

Finally, in addition to age and gender, two demographic variables were included as covariates in the regression analyses. Education was assessed with the question, “What was the highest year level at secondary school you completed?” This item was measured on a 5-point scale, ranging from year 8 or below (5) to year 12 or equivalent (1). Income was included as a proxy measure of socioeconomic status. Income was assessed with the question, “What is your usual, take-home, weekly income from all sources of support (this means after tax is taken out)?” This item was scored on a 10-point scale ranging from $0 (1) to $501 or more (10).

Descriptive statistics for the measures can be found in Table 1.

Table 1.

Descriptive Statistics for Alcohol Use and Covariate Measures.

	M (SD)	Possible Range	α
T1 AUDIT—Alcohol use problems	7.94 (5.11)	1-40	.80
T2 AUDIT—Alcohol use problems	7.00 (4.93)	1-40	.78
T1 Cigarette use	2.43 (1.57)	1-5	NA
T1 Cannabis use	1.93 (1.82)	1-8	NA
T1 Other illicit drug use	1.19 (0.52)	1-8	.78
T1 Antisocial peers	0.21 (0.48)	0-4	.85
T1 Friends’ drug use	1.76 (0.88)	0-4	.82
T1 Peer attachment	3.77 (1.09)	1-5	.69
T1 income	7.32 (2.64)	1-10	NA

Note. NA = not applicable as the measure is based on one item. AUDIT = Alcohol Use Disorders Identification Test.

Analyses

Data were analyzed using the statistical software STATA IC for Windows (version 13; StataCorp, 2013). The analyses consisted of a number of steps. First, attrition was examined. Of those who were originally recruited into the IYDS in 2002, but were not included in the current study due to drop out, 63% (n = 381) were male. Those included in the current sample also had higher scores at the first wave of data collection (collected in 2002 when participants were aged 10-15 years) on measures of frequency of violence (beat someone up) and antisocial behavior (school suspension, stealing, arrest, carrying weapon, attacking someone) than those who did not complete both the young adult waves of the survey (collected in 2010 and 2012). However, there was no difference on measures of lifetime alcohol use measured in 2002 between those who completed the young adult waves and those who did not.

Second, the variance inflation factor (VIF) of each independent variable in each analysis was examined for potential multicollinearity. All VIFs were less than 2.06, indicating no multicollinearity. In Step 3, partially adjusted logistic regression analyses were performed to test relationships between sport participation at T1 and perpetration of each violent behavior (physical IPV, emotional IPV, fighting, and assault) at T2, controlling for T1 violence and demographic variables (specifically, age, gender, education, and income). In Step 4, fully adjusted logistic regression models were performed to test relationships between sport participation at T1 and perpetration of each violent behavior at T2, controlling for T1 violence, demographics, and T1 common risk factors. In Step 5, two-way interactions were added to the fully adjusted models (Sport participation × Alcohol use, Gender × Alcohol use, and Gender × Sport participation). Finally, in Step 6 the three-way interaction (Gender × Alcohol use × Sport participation) was added to these models. Statistically significant interactions were probed using separate regression equations for sport participants and nonparticipants. For all effects, statistical significance was accepted as p < .05.

Results

At T1, 60% (n = 1,347) of the sample participated in sport at least once in the past year. Of the sport participants, 23% participated 1 to 2 times per year, 13% participated 3 to 5 times per year, 9% participated 6 to 9 times per year, 11% participated 10 to 19 times per year, 8% participated 20 to 29 times per year, 5% participated 30 to 39 times per year, and 31% participated 40 or more times per year.

Table 2 reports the rates of violent behaviors and AUDIT scores at each time point, as a function of sport participation (at least once in the past 12 months). Emotional IPV was the most prevalent behavior while assault was the least prevalent. A statistically significantly greater proportion of nonsport participants reported perpetrating physical IPV (at least once in the past 12 months) at both T1 and T2, relative to sport participants. At T1, a statistically significantly greater proportion of nonsport participants also reported emotional IPV, relative to sport participants. There was no statistically significant difference in the proportion of sport participants and nonparticipants reporting fighting or assault at either time points. AUDIT scores were significantly higher for sport participants than for nonparticipants at both time points.

Table 2.

Rates of Violent Behavior and AUDIT Scores, at T1 and T2, as a Function of Sport Participation.

	T1				T2
	Sport Participants	Nonparticipants	Total		Sport Participants	Nonparticipants	Total
	% [95% CI]	% [95% CI]	% [95% CI]	p ^a	% [95% CI]	% [95% CI]	% [95% CI]	p
IPVe	64.05 [61.00, 67.00]	71.67 [68.05, 75.04]	66.97 [64.65, 69.22]	.001	66.10 [63.02, 69.05]	67.90 [64.12, 71.47]	67.03 [64.73, 69.25]	.459
IPVp	13.25 [11.27, 15.52]	21.79 [18.75, 25.16]	16.59 [14.86, 18.49]	<.0001	11.40 [9.53, 13.59]	17.10 [14.33, 20.27]	13.80 [12.22, 15.54]	.001
Fighting	13.17 [11.42, 14.92]	9.94 [8.05, 11.83]	11.85 [10.55, 13.14]	.069	12.69 [10.92, 14.47]	10.05 [8.10, 12.01]	12.16 [10.84, 13.47]	.055
Assault	1.95 [1.23, 2.67]	1.55 [0.77, 2.34]	1.79 [1.26, 2.32]	.755	2.30 [1.50, 3.10]	1.64 [0.82, 2.46]	2.23 [1.64, 2.82]	.274
	T1				T2
	Sport Participants	Nonparticipants	Total		Sport Participants	Nonparticipants	Total
	M (SD)	M (SD)	M (SD)	p ^b	M (SD)	M (SD)	M (SD)	p
AUDIT	8.31 (5.47)	7.36 (5.53)	7.94 (5.11)	.0001	7.40 (4.99)	6.36 (4.74)	7.00 (4.93)	<.0005

Note. Sample size for analyses involving IPV variables = 1,545 at T1 and 1,567 at T2. All other variables n = 2,262. AUDIT = Alcohol Use Disorders Identification Test; CI = confidence interval; IPVe = emotional intimate partner violence, IPVp = physical intimate partner violence; IPV = intimate partner violence.

Chi-square test.

t test.

The results of the partially adjusted logistic regression analyses are reported in Table 3. Each violent behavior at T1 was the strongest predictor of its respective violent behavior at T2. Sport participation was not a statistically significant predictor of any violent behavior at T2. Alcohol use problems at T1 predicted each violent behavior at T2. Females had significantly increased odds of perpetrating IPV (both emotional and physical) but significantly decreased odds of perpetrating assault or engaging in fights.

Table 3.

Partially Adjusted Logistic Regression Analyses for Relationship Between Sport Participation at T1 and Each Violent Behavior at T2.

Dependent Variable	Predictors	OR [95% CI]	p	χ²	Pseudo r²
T2 IPVe	Gender (ref: male)	1.45 [1.09, 1.94]	.011	173.92	.12
	Age	1.02 [0.93, 1.11]	.722
	T1 sport participation (ref: no sport)	0.99 [0.74, 1.32]	.950
	T1 AUDIT	1.06 [1.03, 1.09]	<.0005
	T1 IPVe (ref: no IPVe)	4.87 [3.69, 6.42]	<.0005
	T1 education	1.09 [0.90, 1.33]	.379
	T1 income	1.04 [0.98, 1.10]	.223
T2 IPVp	Gender (ref: male)	1.68 [1.11, 2.54]	.014	118.67	.13
	Age	0.98 [0.87, 1.11]	.796
	T1 sport participation (ref: no sport)	0.96 [0.66, 1.39]	.824
	T1 AUDIT	1.04 [1.00, 1.07]	.024
	T1 IPVp (ref: no IPVp)	6.07 [4.14, 8.89]	<.0005
	T1 education	1.29 [1.05, 1.58]	.016
	T1 income	0.96 [0.88, 1.03]	.268
T2 Fighting	Gender (ref: male)	0.28 [0.20, 0.39]	<.0005	265.23	.18
	Age	0.92 [0.84, 1.02]	.106
	T1 sport participation (ref: no sport)	1.13 [0.83, 1.56]	.436
	T1 AUDIT	1.05 [1.03, 1.08]	<.0005
	T1 Fighting (ref: no fighting)	3.90 [2.78, 5.45]	<.0005
	T1 education	1.41 [1.19, 1.66]	<.0005
	T1 income	1.08 [1.01, 1.15]	.028
T2 Assault	Gender (ref: male)	0.03 [0.00, 0.23]	.001	86.84	.23
	Age	0.88 [0.71, 1.10]	.253
	T1 sport participation (ref: no sport)	1.46 [0.67, 3.19]	.339
	T1 AUDIT	1.06 [1.01, 1.12]	.013
	T1 Assault (ref: no assault)	5.09 [1.84, 14.11]	.002
	T1 education	1.60 [1.15, 2.23]	.005
	T1 income	1.13 [0.96, 1.32]	.131

Note. OR = odds ratio; CI = confidence interval; IPVe = emotional intimate partner violence; AUDIT = Alcohol Use Disorders Identification Test; IPV = intimate partner violence; IPVp = physical intimate partner violence.

Tables 4 to 7 present the fully adjusted logistic regression analyses for each violent behavior. As seen in Table 4, gender (female), T1 emotional IPV and T1 AUDIT were all associated with increased odds of T2 emotional IPV. However, frequency of sport participation at T1 did not predict T2 emotional IPV. There were also no statistically significant two-way or three-way interactions. Similarly, gender (female), T1 physical IPV and T1 cigarette use were all associated with increased odds of T2 physical IPV. There were no statistically significant two or three-way interactions (Table 5).

Table 4.

Fully Adjusted Logistic Regression Analyses for Relationship Between Sport Participation at T1 and Emotional IPV at T2.

Model	Dependent Variable	Predictors	OR [95% CI]	p	χ²	Pseudo r²
1. Main effects	T2 IPVe	Gender (ref: male)	1.61 [1.20, 2.17]	.002	195.74	.14
		Age	1.04 [0.95, 1.14]	.385
		T1 sport participation (ref: no sport)	1.09 [0.81, 1.46]	.583
		T1 AUDIT	1.04 [1.00, 1.07]	.043
		T1 IPV (ref: no IPV)	4.62 [3.49, 6.12]	<.0005
		T1 education	1.01 [0.82, 1.24]	.912
		T1 income	1.03 [0.97, 1.09]	.367
		Antisocial peers	1.40 [0.88, 2.20]	.153
		Friends’ use of drugs	1.23 [0.96, 1.58]	.101
		Peer attachment	0.91 [0.79, 1.05]	.211
		Cigarette use	1.06 [0.96, 1.19]	.256
		Cannabis use	1.08 [0.97, 1.21]	.144
		Other illicit drug use	0.74 [0.52, 1.05]	.092
2. Add two-way interactions	T2 IPVe	Sport participation × T1 AUDIT	0.80 [0.56, 1.14]	.212	199.61	.14
		Gender × T1 AUDIT	0.82 [0.59, 1.14]	.235
		Gender × Sport participation	0.70 [0.38, 1.28]	.249
3. Add three-way interaction	T2 IPVe	Gender × T1 AUDIT × Sport participation	1.03 [0.51, 2.07]	.942	199.62	.14

Note. Model 1 includes only main effects, Model 2 includes main effects plus two-way interactions, Model 3 includes main effects, two-way interactions, and three-way interaction. For the sake of brevity and clarity, only the highest order results from each model are presented. IPV = intimate partner violence; OR = odds ratio; CI = confidence interval; IPVe = emotional intimate partner violence; AUDIT = Alcohol Use Disorders Identification Test.

Table 5.

Fully Adjusted Logistic Regression Analyses for Relationship Between Sport Participation at T1 and Physical IPV at T2.

Model	Dependent Variable	Predictors	OR [95% CI]	p	χ²	Pseudo r²
1. Main effects	T2 IPVp	Gender (ref: male)	1.74 [1.13, 2.67]	.011	135.90	.15
		Age	1.01 [0.89, 1.14]	.922
		T1 sport participation (ref: no sport)	1.05 [0.72, 1.55]	.791
		T1 AUDIT	1.02 [0.98, 1.06]	.402
		T1 IPV (ref: no IPV)	5.67 [3.83, 8.39]	<.0005
		T1 education	1.16 [0.93, 1.45]	.817
		T1 income	0.94 [0.86, 1.01]	.110
		Antisocial peers	1.11 [0.73, 1.69]	.636
		Friends’ use of drugs	1.31 [0.96, 1.79]	.089
		Peer attachment	0.92 [0.77, 1.02]	.398
		Cigarette use	1.21 [1.06, 1.38]	.005
		Cannabis use	0.90 [0.80, 1.01]	.076
		Other illicit drug use	1.13 [0.78, 1.64]	.509
2. Add two-way interactions	T2 IPVp	Sport participation × T1 AUDIT	1.17 [0.80, 1.71]	.416	137.97	.15
		Gender × T1 AUDIT	1.05 [0.71, 1.55]	.804
		Gender × Sport participation	1.36 [0.59, 3.16]	.469
3. Add three-way interaction	T2 IPVp	Gender × T1 AUDIT × Sport participation	1.11 [0.50, 1.48]	.797	137.03	.15

Note. Model 1 includes only main effects, Model 2 includes main effects plus two-way interactions, Model 3 includes main effects, two-way interactions, and three-way interaction. For the sake of brevity and clarity, only the highest order results from each model are presented. IPV = intimate partner violence; OR = odds ratio; CI = confidence interval;AUDIT = Alcohol Use Disorders Identification Test; IPVp = physical intimate partner violence.

Table 6.

Fully Adjusted Logistic Regression Analyses for Relationship Between Sport Participation at T1 and Assault at T2.

Model	Dependent Variable	Predictors	OR [95% CI]	p	χ²	Pseudo r²
1. Main effects	T2 Assault	Gender (ref: male)	0.04 [0.00, 0.28]	.002	115.65	.32
		Age	0.96 [0.75, 1.23]	.749
		T1 sport participation (ref: no sport)	1.93 [0.79, 4.73]	.150
		T1 AUDIT	1.04 [0.98, 1.10]	.249
		T1 Assault (ref: no assault)	3.83 [1.22, 12.08]	.022
		T1 education	1.43 [0.99, 2.06]	.058
		T1 income	1.14 [0.96, 1.36]	.133
		Antisocial peers	2.30 [1.40, 3.78]	.001
		Friends’ use of drugs	1.49 [0.82, 2.72]	.186
		Peer attachment	1.06 [0.73, 1.53]	.771
		Cigarette use	1.02 [0.79, 1.34]	.859
		Cannabis use	0.86 [0.69, 1.07]	.174
		Other illicit drug use	0.90 [0.49, 1.66]	.740
2. Add two-way interactions		Sport participation × T1 AUDIT	1.63 [0.86, 3.10]	.133	118.07	.33
2. Add two-way interactions		Gender × T1 AUDIT	1.17 [0.39, 3.48]	.784
3. Add three-way interaction		Gender × T1 AUDIT × Sport participation	0.98 [0.02, 57.24]	.991	118.07	.33

Note. Model 1 includes only main effects, Model 2 includes main effects plus two-way interactions, Model 3 includes main effects, two-way interactions, and three-way interaction. For the sake of brevity and clarity, only the highest order results from each model are presented. Gender × Sport interaction was not able to be included for this variable as it demonstrated complete separation. OR = odds ratio; CI = confidence interval; AUDIT = Alcohol Use Disorders Identification Test.

Table 7.

Fully Adjusted Logistic Regression Analyses for Relationship Between Sport Participation at T1 and Fighting at T2.

Model	Dependent Variable	Predictors	OR [95% CI]	p	χ²	Pseudo r²
1. Main effects	T2 fighting	Gender (ref: male)	0.29 [0.21, 0.41]	<.0005	306.97	.21
		Age	0.95 [0.86, 1.05]	.308
		T1 sport participation (ref: no sport)	1.34 [0.96, 1.87]	.088
		T1 AUDIT	1.03 [1.00, 1.06]	.031
		T1 fighting (ref: no fights)	3.21 [2.26, 4.56]	<.0005
		T1 education	1.28 [1.07, 1.52]	.007
		T1 income	1.06 [0.99, 1.14]	.071
		Antisocial peers	1.91 [1.42, 2.58]	<.0005
		Friends’ use of drugs	1.06 [0.83, 1.35]	.659
		Peer attachment	0.91 [0.78, 1.05]	.187
		Cigarette use	1.12 [1.00, 1.25]	.049
		Cannabis use	1.02 [0.93, 1.11]	.726
		Other illicit drug use	0.92 [0.70, 1.21]	.551
2. Add two-way interactions	T2 Fighting	Sport participation × T1 AUDIT	1.42 [1.06, 1.89]	.018	318.17	.21
		Gender × T1 AUDIT	0.98 [0.72, 1.33]	.881
		Gender × Sport participation	0.60 [0.29, 1.23]	.165
3. Add three-way interaction	T2 fighting	Gender × T1 AUDIT × Sport participation	0.95 [0.50, 1.80]	.872	316.19	.21

Note. Model 1 includes only main effects, Model 2 includes main effects plus two-way interactions, Model 3 includes main effects, two-way interactions, and three-way interaction. For the sake of brevity and clarity, only the highest order results from each model are presented. OR = odds ratio; CI = confidence interval; AUDIT = Alcohol Use Disorders Identification Test.

As can be seen in Table 6, gender (female) was associated with reduced odds of T2 assault while T1 assault and antisocial peers were associated with increased odds of T2 assault. Again, sport participation at T1 did not predict T2 assault. There were also no statistically significant two-way or three-way interactions.

Finally, as seen in Table 7, gender (female) was associated with reduced odds of T2 fighting while T1 alcohol use problems, T1 fighting, T1 education (low), antisocial peers, and cigarette use were all associated with increased odds of T2 fighting. Although there was no main effect of T1 sport participation on T2 fighting, there was a statistically significant interaction between sport participation and alcohol use problems (no other two-way or three-way interactions reached statistical significance). To probe this interaction, separate logistic regression analyses were completed as a function of sport participation. As can be seen in Table 8, for those who reported participating in sport at least once in the past 12 months, alcohol use problems at T1 were associated with an increased odds of fighting at T2, even when controlling for prior engagement in fights and common risk factors. However, for those who did not report participating in sport in the past 12 months, alcohol use problems at T1 did not significantly predict engagement in fighting at T2. Similarly, antisocial peers and low education were associated with increased odds of fighting at T2 for sport participants but not for nonparticipants.

Table 8.

Fully Adjusted Logistic Regression Analyses for Relationship Between Alcohol Use Problems at T1 and Fighting at T2 for Sport Participant and Nonparticipant Subgroups.

Dependent Variable		Sports Participants				Nonparticipants
Dependent Variable	Predictors	OR [95% CI]	p	χ²	Pseudo r²	OR [95% CI]	p	χ²	Pseudo r²
T2 fighting	Gender (ref: male)	0.23 [0.14, 0.37]	<.0005	252.70	.26	0.40 [0.24, 0.69]	.001	71.43	.14
T2 fighting	Age	0.93 [0.82, 1.06]	.292			1.01 [0.85, 1.20]	.885
	T1 AUDIT	1.05 [1.02, 1.09]	.005			1.00 [0.95, 1.05]	.971
	T1 fighting (ref: no fights)	3.95 [2.56, 6.10]	<.0005			2.30 [1.22, 4.34]	.010
	T1 education	1.46 [1.15, 1.87]	.002			1.07 [0.82, 1.41]	.602
	T1 income	1.03 [0.95, 1.12]	.457			1.11 [0.99, 1.25]	.076
	Antisocial peers	2.30 [1.51, 3.51]	<.0005			1.46 [0.93, 2.29]	.099
	Friends’ use of drugs	0.92 [0.67, 1.28]	.633			1.25 [0.84, 1.85]	.265
	Peer attachment	0.97 [0.80, 1.18]	.757			0.81 [0.64, 1.03]	.085
	Cigarette use	1.15 [0.99,1.33]	.069			1.15 [0.96, 1.38]	.120
	Cannabis use	0.99 [0.87, 0.13]	.905			1.05 [0.93, 1.19]	.431
	Other illicit drug use	0.97 [0.66, 1.43]	.882			0.78 [0.48, 1.26]	.303

Note. OR = odds ratio; CI = confidence interval; AUDIT = Alcohol Use Disorders Identification Test.

Discussion

The current study utilized a large community-based sample of young adults, originally recruited to be state-representative of students in Victoria, Australia, to test longitudinal relationships between sport participation, alcohol use problems, and violent behaviors. The violent behaviors assessed included emotional and physical IPV, fighting, and assault. Contrary to the first hypothesis, when controlling for prior violent behavior, substance use, and common risk factors, sport participation did not predict IPV, fighting, or assault 2 years later. However, consistent with the second hypothesis, sport participation moderated the relationship between problem alcohol use and fighting. For those who participated in sport, problem alcohol use was associated with increased odds of engaging in fights 2 years later, but there was no such relationship between problem alcohol use and fighting for those who did not report sport participation. Finally, the third hypothesis was not supported; gender was not found to moderate the relationship between sport participation, problem alcohol use, and violence.

Contrary to the first hypothesis, the present study did not find any relationships between sport participation and perpetration of violent behavior 2 years later among a community sample of Australian young adults. Although many previous studies have identified relationships between sport participation and violence, there is inconsistency in the types of violent behaviors that have been associated with athletic involvement. For example, a number of studies have found that sport participation is associated with aggressive behaviors, particularly fighting (Burton & Marshall, 2005; Endresen & Oleweus, 2005; O’Brien et al., 2012), whereas, others have not observed such relationships (Gidycz et al., 2007; Miller et al., 2006). Other studies suggest that the relationship between sport participation and violence is dependent on other factors associated with the sport. For example, Nixon (1997) found that athletic involvement in general was not associated with fighting outside of the sporting context, but those who played contact sports or team sports (particularly males) were more likely to engage in fighting outside of sport. Another study found that it was not athletic participation that was associated with fighting, rather it was identifying as a “jock” that predicted engaging in fights (Miller et al., 2006).

The current study did not assess type of sport in which participants engaged (i.e., team sport, contact sport, individual sport), or the social norms of the sporting group with which participants were affiliated. It is possible that some sports or athletic teams foster a culture of aggression, whereas other sports or teams do not (Gidycz et al., 2007; Humphrey & Kahn, 2000). In addition, and perhaps most important, the current study was a community-based sample, rather than an athletic sample, and thus sport participation was measured with regard to participation in community-level sport. A direct effect of sport participation on later violent behavior may be evident in a sample of elite or competitive athletes. Furthermore, the current study was a prospective longitudinal study, unlike most of the published literature to date. In fact, consistent with the current study, relationships between collegiate sport participation and later violence have not been observed in other longitudinal studies (Gidycz et al., 2007; Miller et al., 2006). Future longitudinal research would benefit from more detailed examination of the type of sport, level of identification with the sporting group or culture, level of sport (elite vs. community), and social norms or culture of sporting context to better understand any longitudinal relationships between sport participation and later violence.

While a direct relationship between sport participation and later violent behavior was not observed in the present study, in line with the second hypothesis, sport participation was found to moderate the relationship between problem alcohol use and violent behavior. As such, for those who reported participation in sport in the past 12 months, problem alcohol use was associated with increased odds of fighting 2 years later, whereas, for those who did not report participation in sport, there was no such relationship between problem alcohol use and violence. Furthermore, AUDIT scores were higher for sport participants than nonparticipants. Alcohol use is heavily embedded within community sporting contexts and clubs (Rowland, Toumbourou, & Allen, 2012a). Predetermined and planned drunkenness, where the intention is to get rapidly and heavily intoxicated, is a common occurrence and a rite of passage in many community sporting clubs or organizations; for example, end of season drinking trips, pub crawls, and alcohol-fueled celebrations of wins or commiserations of losses (Palmer, 2011). Such group drinking sessions may help to shape group identities (Griffin, Bengry-Howell, Hackley, Mistral, & Szmigin, 2009) and can foster a sense of belonging or togetherness (Pettigrew, Ryan, & Ogilvie, 2000). This heavy alcohol use, driven by social approval and identification with the group norms and culture, may lead to violent behavior either due to the direct pharmacological effects of intoxication and/or the situational factors associated with intoxication (Wagner, 1996).

In addition, a process of “cultural spillover” may further contribute to making violent behavior more likely among sport participants (Bloom & Smith, 1996). That is, on-field behavior associated with violent or highly competitive sports, “spills over” into inappropriate situations in the individual’s life, such as in public or in intimate relationships (Bloom & Smith, 1996). Based on the current study, this effect may be heightened by the drinking culture of sporting clubs and resultant situations where alcohol is consumed in excess and inhibitions are diminished. Alternatively, this relationship between sport participation, alcohol use, and violence may arise by way of drinking motives. That is, drinking to cope with the pressure and stress associated with participation in competitive sport may lead to a greater likelihood of negative consequences including violence and aggression outside of the sporting context (Martens, Cox, & Beck, 2003; Sonderlund et al., 2014). Both of these possible interpretations suggest that it is not sporting participation per se that leads to alcohol use and violent behavior. Instead, it may be the cognitive or emotional costs of being part of a competitive sporting environment or identification with a particular set of norms or culture (i.e., a drinking culture supported by sporting clubs), which may give rise to particular values and behaviors among the team members (Sonderlund et al., 2014). Such an interpretation is also supported by our finding showing that the covariate affiliation with antisocial peers was a predictor of T2 fighting for sport participants but not nonparticipants. In addition, sport-drinking contexts often promote and are embedded within a culture of hegemonic masculinity (Palmer, 2011), which may further promote the social approval of excessive alcohol consumption and violent behavior. Indeed, drinking context (and the associated dynamics) has long been recognized as an important determinant of alcohol-related violence, with public drinking (as compared with private/residential drinking) a strong predictor of violence (Rossow, 1996; Tomsen, 1997). Similarly, among sporting fans, alcohol has been strongly implicated in spectator aggression and violence in the context of sporting matches (Bormann & Stone, 2001; Moore et al., 2007), with the social dynamics of the spectator crowd thought to contribute to this relationship (Roberts & Benjamin, 2000). Future studies which are able to investigate sport participation in terms of type, level (community vs. elite) and the norms of sport may help to shed further light on the way in which sport participation influences alcohol consumption and later violent behavior.

Though not a focus of the current study, it should be noted that alcohol use, independent of sport participation, was found to predict all types of violence; however, when controlling for covariates such as affiliation with deviant peers’ and friends’ drug use, statistically significant relationships remained only for emotional IPV and fighting. Consistent with other research (Boden, Fergusson, & Horwood, 2012; B. Huang, White, Kosterman, Catalano, & Hawkins, 2001; Scholes-Balog et al., 2013), this suggests that relationships between alcohol use and violence during young adulthood appear to be explained by common social and contextual factors that influence both alcohol use and violence.

Finally, contrary to the third hypothesis, gender was not found to moderate relationships between sport participation, alcohol use, and violence. Miller et al. (2006) found an interaction between “jock” identity and gender in the prediction of nonfamily violence, whereby “jock” identity predicted nonfamily violence for males but not females. Similarly, O’Brien et al. (2012) found that alcohol-related violence and aggression was more likely among male university sport participants than female university sport participants. The current study was a community-based sample, investigating community-level sport participation, whereas the two studies cited above investigated higher level university/college athletes; this may explain the discrepant findings. It should be noted that gender was found to be predictive of violent behavior in the present study (independent of sport participation). Females had reduced odds of perpetrating assault and engaging in fights but increased odds of both types of IPV. Although this may seem counterintuitive, several large representative sample studies have found that dating violence is more likely perpetrated by female than male youths (e.g., Carney, Buttell, & Dutton, 2007; Cui, Ueno, Gordon, & Fincham, 2013). Detailed discussion of why female gender is found to be associated with IPV is beyond the scope of this article; however, numerous hypotheses have been proposed, including that females may have higher levels of empowerment; females may be more likely to report perpetration of IPV; the use of community representative samples may overrepresent common couple violence and underrepresent “intimate terrorism”; it may be more taboo for females to display aggression or violence in public (i.e., fighting and assault in public), and thus violent behavior from women may be more likely to occur in private within the home; and women’s violence against men is less effective and thus may need to be more frequent (Anderson, 2013; Fincham, Cui, Gordon, & Ueno, 2013).

Strengths of this study include its prospective longitudinal design, large representative sample drawn from the community (rather than a college or elite athlete sample), and control for previous violent behavior and other factors that may confound relationships between sport participation, alcohol use, and violence. However, there are some limitations that should be noted. First, the length of the survey from which the current data were drawn precluded use of more detailed measures of violent behavior and sport participation. The measures of fighting and assault were based on single items and did not tap into more specific characteristics such as verbal versus physical violence. Furthermore, the measures of IPV were dichotomized to be consistent with the other measures of violence. Similarly, the measure of sport participation was broad and based on only one item. Therefore, we were not able to distinguish several key features including behavioral (involvement in sport) versus perceptual (perception of one’s self as an athlete) aspects of sport participation, contact versus noncontact sport participation, team or individual sport participation, type of sport (e.g., football vs. tennis), level of sport (compared with community-level sport, high level or elite sport may require a particular personality, which may predispose individuals to be aggressive, and aggression may also be more tolerated or accepted at that level), or identification with the culture and norms of the sport. All of these factors may influence relationships between sport participation, alcohol use, and violence (e.g., Miller et al., 2006; Nixon, 1997). In addition, the current study was self-report and responses may have been influenced by a tendency to respond in a socially desirable manner with regard to sensitive topics such as perpetration of violence. Nonetheless, research suggests that self-report methods are a valid and reliable means of assessing violence and delinquency (Thornberry & Krohn, 2000).

The findings of the current study suggest that the drinking culture and social approval of excessive alcohol consumption within community sporting environments should be a prime target for prevention efforts to reduce violent behavior among sport participants. Studies of U.S. college athletes have found a high level of exposure to educational programs regarding alcohol through the work of the National College Athletic Association (NCAA) as well as from individual athletic departments (Nelson & Wechsler, 2001). Despite this education about the risks of alcohol consumption, high rates of binge drinking are still observed (Nelson & Wechsler, 2001). Interventions that tap into the athletic culture and quash the social pull toward risky alcohol consumption have been suggested to potentially be effective. In Victoria, Australia, the VicHealth Healthy Sporting Environments Program supports community sporting clubs to become healthier by achieving minimum standards relating to six key factors that shape people’s experience in a sporting club and impact on health. One of these factors is to ensure that alcohol is served and consumed responsibly (Centre for Sport and Social Impact, 2013). The Good Sports program has also been developed to reduce risky alcohol consumption and alcohol-impaired driving in community sports clubs. Evaluations of this program to date have suggested that it is associated with lower levels of risky alcohol consumption and reduced risk of drink driving (Rowland et al., 2012a; Rowland, Toumbourou, & Allen, 2012b). Such programs, which target the culture of risky alcohol consumption in sporting contexts may also have a beneficial secondary influence on alcohol-fueled violent behavior, particularly fighting, among the sports participants. However, it should be acknowledged that the strongest predictor of violent behavior for both sports participants and nonparticipants was prior violent behavior. As such, in addition to targeting a culture of risky drinking in sporting clubs, it may be important for clubs to identify and support (e.g., anger management skills, interpersonal communication, conflict resolution) individuals within the club who have a history of violent behavior or fights.

In summary, among a large sample of Australian young adults, sport participation was not found to be predictive of perpetration of IPV, assault, or fighting 2 years later. However, sport participation was found to moderate the relationship between problem alcohol use and fighting. These findings have implications for understanding potential circumstances and mechanisms by which involvement in sports may lead to involvement in violent behaviors. Further longitudinal studies are necessary to examine how the particular sporting contexts and their associated cultures influence alcohol consumption and violence. The current findings suggest that intervention and prevention approaches should address the drinking culture and social approval of excessive alcohol consumption embedded within sporting contexts. Interventions to discourage excessive alcohol consumption, targeted at sports settings and young people who engage in sport, may reduce the incidence of violent fighting off-field.

Footnotes

Acknowledgements

The authors also wish to thank the participants for their valuable contribution.

Authors’ Note

The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute on Drug Abuse, the National Institutes of Health, or Australian funders.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Grant support for the original International Youth Development Study data collection was provided by the National Institute on Drug Abuse (R01-DA012140-05) and for the young adult follow-up by the Australian National Health and Medical Research Council (Projects 594793 and 1047902), and the Australian Research Council (Discovery Project, DP109574).

Author Biographies

Kirsty E. Scholes-Balog is a postdoctoral research fellow in the Learning Sciences Institute Australia at Australian Catholic University. She received her PhD in Medicine in 2010 from the University of Western Australia. Her current research interests include substance use, mental health, and problem behaviors (particularly problem online behaviors) among adolescents and young adults.

Sheryl A. Hemphill is a professor of psychology at Australian Catholic University. She completed her PhD in psychology at La Trobe University, Australia. Her research focuses on the development and prevention of antisocial behavior and related problem behaviors, with a focus on family and school contexts.

Peter J. Kremer, PhD, is a senior lecturer in the School of Exercise and Sport Sciences at Deakin University, Australia. He received his PhD from the University of Melbourne in 2005. His research focuses on the relationship between involvement in sport and exercise and health and well-being outcomes.

John W. Toumbourou is the associate dean (partnerships and workplace), in the Faculty of Health and the professor and chair in health psychology within the School of Psychology at Deakin University, Australia. He is an associate director of the Deakin Strategic Centre for Mental Health and Wellbeing Research and a prominent social advocate in areas related to child and adolescent mental health promotion and the prevention of alcohol and drug problems. He plays a leadership role in assisting the development of partnerships and research capacity within the School and Faculty. He has been influential internationally and nationally in assisting the development of research and practice in the fields of prevention science and health psychology. He has received international awards for his contributions in these areas and has been influential in reshaping Australian health policies to more effectively address adolescent alcohol misuse and related problems.

References

Anderson

K. L.

(2013). Why do we fail to ask “why” about gender and intimate partner violence. Journal of Marriage and Family, 75, 314-318.

Babor

T. F.

de la Fuente

J. R.

Saunders

Grant

(1992). The Alcohol Use Disorders Identification Test: Guidelines for use in primary health care. Geneva, Switzerland: World Health Organization.

Bloom

G. A.

Smith

M. D.

(1996). Hockey violence: A test of cultural spillover theory. Sociology of Sport Journal, 13, 65-77.

Boden

J. M.

Fergusson

D. M.

Horwood

L. J.

(2012). Alcohol misuse and violent behavior: Findings from a 30-year longitudinal study. Drug and Alcohol Dependence, 122, 135-141.

Bormann

C. A.

Stone

M. H.

(2001). The effects of eliminating alcohol in a college stadium: The Folsom Field beer ban. Journal of American College Health, 50, 81-88.

Burton

J. M.

Marshall

L. A.

(2005). Protective factors for youth considered at risk of criminal behaviour: Does participation in extracurricular activities help? Criminal Behaviour and Mental Health, 15, 46-64.

Carney

Buttell

Dutton

(2007). Women who perpetrate intimate partner violence: A review of the literature with recommendations for treatment. Aggression and Violent Behavior, 12, 108-115.

Centre for Sport and Social Impact. (2013). Healthy sporting environments demonstration project: Final evaluation report (technical) for Leisure Networks and the Victorian Health Promotion Foundation. Melbourne, Australia: La Trobe University.

Cui

Ueno

Gordon

Fincham

F. D.

(2013). The continuation of intimate partner violence from adolescence to young adulthood. Journal of Marriage and Family, 75, 300-313.

10.

Dembo

Williams

Getreu

Genung

Schmeidler

Berry

. . . La Voie

(1993). Longitudinal study of the relationship among marijuana/hashish use, cocaine use and delinquency in a cohort of high risk youths. Journal of Drug Issues, 21, 271-312.

11.

Dietze

P. M.

Fitzgerald

J. L.

Jenkinson

R. A.

(2008). Drinking by professional Australian Football League (AFL) players: Prevalence and correlates of risk. The Medical Journal of Australia, 189, 479-483.

12.

Ellickson

P. L.

Tucker

J. S.

Klein

D. J.

(2003). Ten-year prospective study of public health problems association with early drinking. Pediatrics, 111, 949-955.

13.

Endresen

I. M.

Oleweus

(2005). Participation in power sports and antisocial involvement in preadolescent and adolescent boys. Journal of Child Psychology and Psychiatry, 46, 468-478.

14.

Exum

M. L.

(2006). Alcohol and aggression: An integration of findings from experimental studies. Journal of Criminal Justice, 34, 131-145.

15.

Fincham

F. D.

Cui

Gordon

Ueno

(2013). What comes before why: Specifying the phenomenon of intimate partner violence. Journal of Marriage and Family, 75, 319-324.

16.

Fleming

M. F.

Barry

K. L.

Macdonald

(1991). The Alcohol Use Disorders Identification Test (AUDIT) in a college sample. Substance Use & Misuse, 26, 1173-1185.

17.

Frinter

M. P.

Rubinson

(1993). Acquaintance rape: The influence of alcohol, fraternity membership, and sports team membership. Journal of Sex Education and Therapy, 19, 272-284.

18.

Gidycz

C. A.

Warkentin

J. B.

Orchowski

L. M.

(2007). Predictors of perpetration of verbal, physical, and sexual violence: A prospective analysis of college men. Psychology of Men & Masculinity, 8, 79-94.

19.

Glaser

R. R.

Lee Van Horn

Arthur

M. W.

Hawkins

Catalano

R. F.

(2005). Measurement properties of the Communities That Care Youth Survey across demographic groups. Journal of Quantitative Criminology, 21, 73-102.

20.

Gmel

Kuendig

Daeppen

(2009). Sport and alcohol: An emergency department study in Switzerland. European Journal of Sport Science, 9, 11-22.

21.

Griffin

Bengry-Howell

Hackley

Mistral

Szmigin

(2009). “Every time I do it, I absolutely annihilate myself”: Loss of (self) consciousness and loss of memory in young people’s drinking narratives. Sociology, 43, 457-476.

22.

Hemphill

S. A.

Heerde

J. A.

Herrenkohl

T. I.

Patton

G. C.

Toubourou

J. W.

Catalano

R. F.

(2011). Risk and protective factors for adolescent substance use in Washington State, The United States and Victoria, Australia: A longitudinal study. Journal of Adolescent Health, 49, 312-320. doi:10.1016/j.jadohealth.2010.12.017

23.

Herrenkohl

T. I.

McMorris

B. J.

Catalano

R. F.

Abbott

R. D.

Hemphill

S. A.

Toumbourou

J. W.

(2007). Risk factors for violence and relational aggression in adolescence. Journal of Interpersonal Violence, 22, 386-405.

24.

Huang

White

H. R.

Kosterman

Catalano

R. F.

Hawkins

J. D.

(2001). Developmental associations between alcohol and interpersonal aggression during adolescence. Journal of Research in Crime & Delinquency, 38, 64-83.

25.

Huang

D. B.

Cherek

D. R.

Lane

S. D.

(1999). Laboratory measurement of aggression in high school age athletes: Provocation in a nonsporting context. Psychological Reports, 85, 1251-1262.

26.

Humphrey

S. E.

Kahn

A. S.

(2000). Fraternities, athletic teams, and rape: Importance of identification with a risky group. Journal of Interpersonal Violence, 15, 1313-1322.

27.

Kimble

N. B.

Russo

S. A.

Bergman

B. G.

Galindo

V. H.

(2010). Revealing an empirical understanding of aggression and violent behavior in athletics. Aggression and Violent Behavior, 15, 446-462.

28.

Koss

M. P.

Gaines

J. A.

(1993). The prediction of sexual aggression by alcohol use, athletic participation, and fraternity affiliation. Journal of Interpersonal Violence, 8, 94-108.

29.

Leichliter

J. S.

Meilman

P. W.

Presley

C. A.

Cashin

J. R.

(1998). Alcohol use and related consequences among students with varying levels of involvement in college athletics. Journal of American College Health, 46, 257-262.

30.

Linville

D. C.

Huebner

A. J.

(2005). The analysis of extracurricular activities and their relationship to youth violence. Journal of Youth and Adolescence, 34, 483-492.

31.

Martens

M. P.

Cox

R. H.

Beck

N. C.

(2003). Negative consequences of intercollegiate athlete drinking: The role of drinking motives. Journal of Studies on Alcohol, 64, 825-829.

32.

McMorris

B. J.

Catalano

R. F.

Kim

M. J.

Toumbourou

J. W.

Hemphill

S. A.

(2011). Influence of family factors and supervised alcohol use on adolescent alcohol use and harms: Similarities between youth in different alcohol policy contexts. Journal of Studies on Alcohol and Drugs, 72, 418-428.

33.

McMorris

B. J.

Hemphill

S. A.

Toumbourou

J. W.

Catalano

R. F.

Patton

G. C.

(2007). Prevalence of substance use and delinquent behaviour in adolescents from Victoria, Australia and Washington State, United States. Health Education & Behavior, 34, 634-650.

34.

Miller

K. E.

Melnick

M. J.

Farrell

M. P.

Sabo

D. F.

Barnes

G. M.

(2006). Jocks, gender, binge drinking and adolescent violence. Journal of Interpersonal Violence, 21, 105-120.

35.

Moore

S. C.

Shepherd

J. P.

Eden

Sivarajasingam

(2007). The effect of rugby match outcome on spectator aggression and intention to drink alcohol. Criminal Behaviour and Mental Health, 17, 118-127.

36.

Murnen

S. K.

Kohlman

M. H.

(2007). Athletic participation, fraternity membership, and sexual aggression among college men: A meta-analytic review. Sex Roles, 57, 145-157.

37.

Nelson

T. F.

Wechsler

(2001). Alcohol and college athletes. Medicine & Science in Sports & Exercise, 33, 43-47.

38.

Newcomb

M. D.

McGee

(1989). Adolescent alcohol use and other delinquent behaviors: A one-year longitudinal analysis controlling for sensation seeking. Criminal Justice and Behavior, 16, 345-369.

39.

Nixon

H. L.

(1997). Gender, sport, and aggressive behavior outside sport. Journal of Sport & Social Issues, 21, 379-391.

40.

O’Brien

K. S.

Ali

Cotter

O’Shea

R. P.

Stannard

(2007). Hazardous drinking in New Zealand sportspeople: Level of sporting participation and drinking motives. Alcohol and Alcoholism, 42, 376-382.

41.

O’Brien

K. S.

Blackie

J. M.

Hunter

J. A.

(2005). Hazardous drinking in elite New Zealand sportspeople. Alcohol and Alcoholism, 40, 239-241.

42.

O’Brien

K. S.

Kolt

G. S.

Martens

M. P.

Ruffman

Miller

P. G.

Lynott

(2012). Alcohol-related aggression and antisocial behaviour in sportspeople/athletes. Journal of Science and Medicine in Sport, 15, 292-297.

43.

O’Brien

K. S.

Kolt

G. S.

Webber

Hunter

J. A.

(2010). Alcohol consumption in sport: The influence of sporting idols, friends and normative drinking practices. Drug and Alcohol Review, 29, 676-683.

44.

Palmer

(2011). Key themes and research agendas in the sport-alcohol nexus. Journal of Sport & Social Issues, 35, 168-185.

45.

Pappas

N. T.

McKenry

P. C.

Skilken Catlett

(2004). Athlete aggression on the rink and off the ice: Athlete violence and aggression in hockey and interpersonal relationships. Men and Masculinities, 6, 291-312.

46.

Pettigrew

Ryan

Ogilvie

(2000). New year’s eve consumption plans: Consumers’ consumption priorities on the eve of 2000. Australian Marketing Journal, 9(2), 66-75.

47.

Poortinga

(2007). Associations of physical activity with smoking and alcohol consumption: A sport or occupation effect? Preventive Medicine: An International Journal Devoted to Practice and Theory, 45, 66-70.

48.

Roberts

Benjamin

(2000). Spectator violence in sports: A North American perspective. European Journal on Criminal Policy and Research, 8, 163-181.

49.

Rossow

(1996). Alcohol-related violence: The impact of drinking pattern and drinking context. Addiction, 91, 1651-1661.

50.

Rowland

Toumbourou

J. W.

Allen

(2012a). Drink-driving in community sporting clubs: Adopting the Good Sports alcohol management program. Accident Analysis & Prevention, 48, 264-270.

51.

Rowland

Toumbourou

J. W.

Allen

(2012b). Reducing drink-driving in community sports clubs: Testing the Good Sports program. Journal of Studies on Alcohol and Drugs, 73, 316-327.

52.

Scholes-Balog

K. E.

Hemphill

S. A.

Kremer

Toumbourou

J. W.

(2013). A longitudinal study of the reciprocal effects of alcohol use and interpersonal violence among Australian young people. Journal of Youth and Adolescence, 42, 1811-1823. doi:10.1007/s10964-013-9910-z

53.

Segrave

Moreau

Hastad

D. N.

(1985). An investigation into the relationship between ice hockey participation and delinquency. Sociology of Sport Journal, 2, 281-299.

54.

Sonderlund

A. L.

O’Brien

Kremer

Rowland

DeGroot

Staiger

. . .Miller

P. G.

(2014). The association between sports participation, alcohol use and aggression and violence: A systematic review. Journal of Science and Medicine in Sport, 17, 2-7. doi:10.1016/j.jsams.2013.03.011

55.

StataCorp. (2013). Stata Statistical Software: Release 13. College Station, TX: StataCorp.

56.

Straus

M. A.

Hamby

S. L.

Boney-McCoy

Sugarman

D. B.

(1996). The Revised Conflict Tacts Scales (CTS2). Journal of Family Issues, 17, 283-316.

57.

Thornberry

T. P.

Krohn

M. D.

(2000). The self-report method for measuring delinquency and crime. Measurement and Analysis of Crime and Justice, 4, 33-83.

58.

Tomsen

(1997). A top night: Social protest, masculinity and the culture of drinking violence. British Journal of Criminology, 37, 90-102.

59.

Wagner

E. F.

(1996). Substance use and violent behavior in adolescence. Aggression and Violent Behavior, 1, 375-387.

60.

White

H. R.

Loeber

Stouthamer-Loeber

Farrington

D. P.

(1999). Developmental associations between substance use and violence. Development and Psychopathology, 11, 785-803.

61.

Windle

(1990). A longitudinal study of antisocial behaviors in early adolescence as predictors of late adolescent substance use: Gender and ethnic group differences. Journal of Abnormal Psychology, 99, 86-91.

62.

Zue

Zimmerman

M. A.

Cunningham

(2009). Relationship between alcohol use and violent behavior among urban African American youths from adolescence to emerging adulthood: A longitudinal study. American Journal of Public Health, 99, 2041-2047.