Problem Gambling and Family Violence: Factors Associated With Family Violence Victimization and Perpetration in Treatment-Seeking Gamblers

Abstract

Although problem gambling and family violence are related, there is little available research exploring the factors associated with this relationship. The primary aim was to predict family violence (victimization and perpetration) in a sample of treatment-seeking gamblers by gambling indices (gambling symptom severity, gambling time spent, gambling frequency, gambling expenditure), psychological distress, post-traumatic stress disorder (PTSD) symptoms, gambling coping motives, alcohol and drug use, gambling-related legal consequences, work and social adjustment, impulsivity, and gender. A secondary aim was to explore the degree to which these factors moderate the relationship between gambling symptom severity and family violence. Participants (n = 141) were consecutively recruited gamblers presenting to a gambling counseling service. The prevalence of family violence was 25.5%, with 18.4% reporting victimization and 19.1% reporting perpetration. Intimate partners and parents were most likely to be both perpetrators and victims of family violence. Victimization was significantly predicted by psychological distress, symptoms of PTSD, and gambling-related legal consequences, while perpetration was significantly predicted by gambling symptom severity, gambling-related legal consequences, and impulsivity. The association between gambling symptom severity and victimization was significant only for gamblers with low levels of gambling coping motives and moderate or high levels of alcohol use. These findings provide further support for routine screening in problem gambling and family violence services, particularly those who report gambling-related legal consequences; highlight the need for prevention and intervention programs to lower the co-occurrence of these behaviors; and suggest that reducing psychological distress, symptoms of PTSD, alcohol use, and impulsivity may be important in these efforts.

Keywords

problem gambling family violence victimization perpetration psychological distress alcohol impulsivity

Gambling is a significant public health problem in the many countries, with an estimated 0.5% to 7.6% of the adult population experiencing gambling disorders worldwide, with an average rate across all countries being 2.3% (Williams, Volberg, & Stevens, 2012). Gambling disorder (formerly pathological gambling), which refers to persistent and recurrent problematic gambling behavior leading to clinically significant impairment or distress, is classified as an addiction and related disorder in the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM-5; American Psychiatric Association, 2013). Increasingly, however, the term “problem gambling” is used to describe harms associated with difficulties in limiting time and/or money spent on gambling (Neal, Delfabbro, & O’Neil, 2005; Williams et al., 2012), and is intended to encompass a continuum of severity that includes the diagnostic classification of pathological or disordered gambling. Researchers estimate that the gambling problem of one individual has direct negative effects on at least six others, including spouses and intimate partners (Goodwin, Browne, Rockloff, & Rose, 2017). A growing body of evidence confirms that problem gambling significantly disrupts dyadic relationships and family environments and adversely affects the emotional and physical health of partners and children (Chan, Dowling, Jackson, & Shek, 2016; Dowling, Rodda, Lubman, & Jackson, 2014; Dowling, Smith, & Thomas, 2009; Dowling, Suomi, Jackson, & Lavis, 2016; Langham et al., 2016).

Problem Gambling and Intimate Partner Violence (IPV)

There is also limited, but growing, international evidence that problem gambling is associated with IPV (Dowling, Suomi, Jackson, Lavis, Patford, et al., 2016). The World Health Organization (2013) defines IPV as any behavior within an intimate relationship that causes physical, psychological, or sexual harm to those in that relationship, which can include acts of physical violence, sexual violence, emotional (psychological) abuse, and controlling behaviors. A recent systematic review (Dowling, Suomi, Jackson, Lavis, Patford, et al., 2016) identified six quantitative studies exploring the relationship between problem gambling and IPV victimization and 10 quantitative studies exploring the relationship between problem gambling and IPV perpetration. Although there were some equivocal findings, the review found that problem gambling was consistently associated with both the victimization and perpetration of IPV.

The precise nature of the relationship between problem gambling and IPV, however, remains unknown. Individual coping theoretical perspectives argue that some people, particularly women, employ gambling as a mechanism to physically or emotionally escape distress resulting from IPV victimization experiences (Afifi, Brownridge, MacMillan, & Sareen, 2010; Cunningham-Williams, Abdallah, Callahan, & Cottler, 2007; Dowling, Suomi, Jackson, Lavis, Patford, et al., 2016; Echeburua, Gonzalez-Ortega, de Corral, & Polo-Lopez, 2011; Korman et al., 2008). Similarly, some researchers hypothesize that problem gambling may be consequent to the perpetration of IPV (Brasfield et al., 2012; Dowling, Suomi, Jackson, Lavis, Patford, et al., 2016; Korman et al., 2008). They suggest that this relationship may be mediated, in part, by alcohol use (Brasfield et al., 2012) or a need to regulate anger associated with the perpetration of IPV (Korman et al., 2008).

An alternative theoretical perspective is that the stress and strain of living with a problem gambling intimate partner results in IPV (Dowling, Suomi, Jackson, Lavis, Patford, et al., 2016; Orford, Copello, Velleman, & Templeton, 2010). It is possible that gambling-related stressors, such as the loss of family financial resources, abdication of family role responsibilities, mistrust, and poor communication may result in chronic family stress, domestic conflict, and the perpetration of violence by intimate partners (Dowling, Suomi, Jackson, Lavis, Patford, et al., 2016; Echeburua et al., 2011; Korman et al., 2008). Similarly, one hypothesis put forward to explain the relationship between problem gambling and the perpetration of IPV is that gambling losses and other problems may result in the manifestation of stress, anger, and financial crisis within the home and lead to the perpetration of violence by gamblers against their intimate partners (Afifi et al., 2010; Dowling, Suomi, Jackson, Lavis, Patford, et al., 2016; Korman et al., 2008; Muelleman, DenOtter, Wadman, Tran, & Anderson, 2002). It has been posited that problem gambling may contribute to relationship distress and risk of alcohol abuse, which in turn may increase violent behaviors (Brasfield et al., 2012; Brasfield, Shorey, Febres, Strong, & Stuart, 2011).

To date, these perspectives are theoretical and have been hypothesized without reference to empirical evidence. Although there are currently no longitudinal or event-level studies exploring the temporal nature of the relationship between problem gambling and IPV, there is preliminary empirical evidence from the retrospective accounts from samples of problem gamblers and their family members that problem gambling most often precedes, or coincides with, both IPV victimization and perpetration (Suomi et al., 2021; Suomi et al., 2013). These findings therefore support the theoretical perspective that the stress and strain of living with a problem gambling intimate partner results in IPV (Dowling, Suomi, Jackson, Lavis, Patford, et al., 2016; Orford et al., 2010).

Researchers also suggest that that some common underlying factors, such as a history of victimization, anger problems, emotion dysregulation, impulsivity, and psychiatric comorbidity, may lead to a greater risk for both problem gambling and IPV (Brasfield et al., 2012; Korman et al., 2008; Muelleman et al., 2002). Taken together, these hypothesized relationships implicate a range of variables in the problem gambling–IPV association, including psychological distress, trauma, coping motives, alcohol and drug use, gambling impacts, impulsivity, and gender (Dowling, Suomi, Jackson, Lavis, Patford, et al., 2016). Only a small number of empirical studies, however, have investigated the role of these factors (Dowling, Suomi, Jackson, Lavis, Patford, et al., 2016).

There is some evidence that psychiatric disorders attenuate the associations between problem gambling and both physical IPV victimization and perpetration (Afifi et al., 2010; Roberts et al., 2016; Roberts et al., 2017), although anxiety and depression have not been associated with IPV victimization (type not specified) in problem gamblers (Echeburua et al., 2011). Although alcohol and drug use problems have not influenced the relationship between problem gambling and physical, psychological, or sexual IPV victimization (Echeburua et al., 2011; Korman et al., 2008; Schluter, Abbott, & Bellringer, 2008), almost all available studies implicate alcohol and drug use in the relationship between problem gambling and physical, psychological, and sexual IPV perpetration (Brasfield et al., 2012; Brasfield et al., 2011; Goldstein, Walton, Cunningham, Resko, & Duan, 2009; Muelleman et al., 2002). Similarly, although impulsivity has not been associated with victimization (type not specified) in problem gamblers (Echeburua et al., 2011), it has been positively associated with both problem gambling and the perpetration of IPV (physical, psychological, and sexual) in male batterers (Brasfield et al., 2012).

The hypothesized relationships between problem gambling and IPV also implicate gender. Although there are some findings that female treatment-seeking gamblers are more likely than male gamblers to report physical, psychological, or sexual IPV victimization (Palmer du Preez et al., 2018) and IPV injury perpetration (Korman et al., 2008), male and female gamblers generally display similar rates of physical, psychological, and sexual IPV (Korman et al., 2008; Suomi et al., 2019). Moreover, gender has failed to moderate the relationship between gambling symptom severity and physical IPV perpetration in a community sample (Afifi et al., 2010).

Problem Gambling and Family Violence

In addition to violence between partners, there is an emerging literature suggesting that problem gambling is also associated with family violence, which encompasses violence occurring between family members, such as violence between siblings or across generations (Dowling, Suomi, Jackson, Lavis, Patford, et al., 2016). This includes “a wide range of physical, emotional, sexual, social, spiritual, cultural, psychological, and economic abuses that occur within families, intimate relationships, extended families, kinship networks and communities” (Victorian Department of Human Services, 2012, p. 4). Between 20% and 64% of problem gamblers report victimization experiences (physical, psychological, or sexual) by family members (Dowling et al., 2018; Dowling, Jackson, et al., 2014; Kausch, Rugle, & Rowland, 2006; Palmer du Preez et al., 2018; Raylu & Oei, 2009; Suomi et al., 2013), and between 20% and 41% of problem gamblers report perpetrating violence (physical, psychological, or sexual) toward family members (Dowling et al., 2018; Dowling, Jackson, et al., 2014; Palmer du Preez et al., 2018; Suomi et al., 2013). In these studies, parents and intimate partners are most likely to be both perpetrators and victims of physical, psychological, or sexual family violence (Dowling et al., 2018; Dowling, Jackson, et al., 2014; Suomi et al., 2019; Suomi et al., 2013).

In the only study to explore the role of psychosocial characteristics in the relationships between problem gambling and violence that extend beyond intimate partners, Dowling et al. (2018) found that the associations between problem gambling and both family violence victimization and perpetration (physical, psychological, or sexual) in an Australian population-representative study remained robust for low-risk gamblers, but were generally attenuated for moderate-risk/problem gamblers, to adjustment for substance use (hazardous alcohol use, cannabis use, other substance use) and psychological distress. Moreover, moderate-risk/problem gamblers had a greater probability of family violence victimization if they reported hazardous alcohol use.

There are also mixed findings in relation to the role of gender in the relationship between problem gambling and violence (physical, psychological, or sexual) extending into the broader family. Suomi et al. (2019) found no gender differences in family violence in a sample of treatment-seeking gamblers. This is in contrast to the findings of the larger study from which their sample was selected, in which female gamblers from treatment services were significantly more likely to report family violence victimization than male gamblers (Dowling, Jackson, et al., 2014). In contrast, Palmer du Preez et al. (2018) found that female treatment-seeking gamblers are more likely than their male counterparts to report both family violence perpetration and victimization. Moreover, in a community sample, Dowling et al. (2018) found that low-risk gamblers had a greater probability of family violence perpetration if they were women.

Research Aims

Further research is clearly required to identify the factors associated with the relationship between problem gambling and violence that extends into the family beyond intimate partners. The current study therefore aims to expand on past research by exploring the factors associated with family violence victimization and perpetration in a sample of treatment-seeking gamblers. The primary aim was to predict family violence (victimization and perpetration) by gambling indices (gambling symptom severity, gambling time spent, gambling frequency, gambling expenditure), psychological distress, symptoms of post-traumatic stress disorder (PTSD), gambling coping motives, alcohol and drug use, gambling-related legal consequences, work and social adjustment, impulsivity, and gender. Given the limited variability in gambling symptom severity scores in treatment-seeking gamblers (Dowling, Suomi, Jackson, Lavis, Patford, et al., 2016), the secondary aim was to explore the degree to which these factors moderate the relationship between gambling symptom severity and family violence. Findings from the current study can be used to inform the future development of appropriate and effective protocols for the screening, assessment, and treatment of problem gambling and family violence.

Method

Participants

The sample comprised 141 new voluntary clients (100 male, 39 female, two unspecified gender) to a specialist problem gambling service in central Melbourne, Australia. The participants were a subset of the 463 treatment-seeking gamblers screened for family violence in a previous study (Dowling, Jackson, et al., 2014). The current sample comprised the participants from one of the eight participating gambling services in the previous study. This sample was selected for investigation because the family violence screening items were added to the intake survey completed by clients on presentation to the service; this survey comprised a range of measures that were not available in the larger study.

The majority of participants were born in Australia (67%), with a smaller proportion of participants born in Europe (16%), Asia (14%), and the Pacific Region (3%). The age of the participants ranged from 21 to 74 years (M = 39.63, SD = 11.33, median = 39). Over half (55%) were engaged in full-time employment, with smaller proportions unemployed (29%) or employed part-time (17%). Participants’ fortnightly income ranged from AUD216 to AUD16,000 (M = AUD1,697; SD = AUD1,813; median = AUD1,336). Gambling expenditure per fortnight ranged from AUD10 to AUD15,000 (M = AUD792; SD = AUD1,540; median = AUD400). The primary gambling activity was electronic gaming machines (EGMs) for over half of the participants (55%), with the remaining participants reporting wagering (35%) or playing casino style games (9%) as their primary gambling type. Scores on the Problem Gambling Severity Index (PGSI: Ferris & Wynne, 2001) ranged from 3 to 29 (M = 17.7, SD = 6.0, median = 19), with 5.7% classified in the moderate-risk gambling category and 94.3% classified in the problem gambling category.

Measures

Participants were requested to complete a self-report survey measuring family violence, gambling indices (gambling symptom severity, gambling time spent, gambling frequency, gambling expenditure), psychological distress, symptoms of PTSD, gambling coping motives, alcohol and drug use, gambling-related legal consequences, work and social adjustment, and impulsivity.

Family violence

The four-item Hurt–Insult–Threaten–Scream (HITS) Scale (Sherin, Sinacore, Li, Zitter, & Shakil, 1998) asks how often partners or family members physically Hurt, Insult, Threatened with harm or Screamed at them. The HITS scale was modified into single items measuring family violence victimization (In the past twelve months, has a family member physically hurt you, insulted or talked down to you, threatened you with harm or screamed or cursed at you?) and perpetration (In the past twelve months, have you physically hurt, insulted or talked down to, threatened with harm, or screamed or cursed at a family member?). Participants were provided with a definition of family members and those endorsing either item were asked to specify their relationship to the relevant immediate or extended family member(s). The original HITS displays high internal consistency (α = .80) and good concurrent and construct validity (Sherin et al., 1998). The HITS was selected due to its brevity, psychometric properties, and its ability to be converted into a brief screening tool that measures violence extending beyond intimate partners and for perpetration experiences (see Rabin, Jennings, Campbell, & Bair-Merritt, 2009; Thompson, Basile, Hertz, & Sitterle, 2006). The items were modified into single items to reduce participant burden during the screening process.

Gambling indices

Gambling symptom severity was measured using the nine-item PGSI (Ferris & Wynne, 2001). Respondents indicated how often each item applied to them in the past 12 months on a 4-point scale ranging from 0 (never) to 3 (almost always). Scores range from 0 to 27 and higher scores indicate higher problem severity. The PGSI has been adopted as the preferred measurement tool for population-level research in Australia (Neal et al., 2005). The PGSI has displayed good internal consistency in previous research (Dowling, Youssef, et al., 2016; Ferris & Wynne, 2001) and the current study (α = .85). Other indices of gambling behavior relating to their primary gambling activity were measured with single items: In a typical fortnight, about how much time would you spend gambling (in hours)? (time spent); In a typical fortnight, over roughly how many sessions would this be? (frequency); and In a typical fortnight, about how much money did you lose in total (net loss)? (expenditure).

Psychological distress

The Kessler–6 (K6: Kessler et al., 2002) is a validated measure of past month nonspecific psychological distress. This six-item scale, which has been widely used in population epidemiologic studies, comprises six questions asking respondents to indicate how frequently they experience specific symptoms of psychological distress, such as nervousness, agitation, psychological fatigue, and depression. Each item has a 5-point response format ranging from 1 (none of the time) to 5 (all of the time), with higher scores indicating greater psychological distress. The items of the K6 have displayed excellent reliability in previous research (Dowling, Youssef, et al., 2016; Kessler et al., 2002) and in the present study (α = .91).

Symptoms of PTSD

The four-item Primary Care–Post-Traumatic Stress Disorder (PC-PTSD: Prins et al., 2004) was employed to measure PTSD. Each item in the scale corresponds to the four factors (i.e., re-experiencing, avoidance, hyperarousal, and numbing) found to be specific to the construct of PTSD and not confounded by general psychological distress (Foa, Riggs, & Gershuny, 1995). Items are endorsed using a yes/no format. The PC-PTSD has been found to have good test–retest reliability and has evidenced good operating characteristics when compared with PTSD diagnoses based on research interviews (Prins et al., 2004). The PC-PTSD has displayed good internal consistency in previous research (Brown, Oldenhof, Allen, & Dowling, 2016; Prins et al., 2004) and in the present study (α = .81).

Gambling coping motives

The five-item Coping Motives subscale of the Gambling Motivation Questionnaire (GMQ: Stewart & Zack, 2008) was employed to evaluate gambling for internal negative reinforcement (i.e., gambling to reduce or avoid negative emotions). Respondents indicate how often they think they gamble for each reason on a 4-point scale from 1 (almost never/never) to 4 (almost always). The Coping Motives subscale has demonstrated good internal consistency in previous research (Lambe, Mackinnon, & Stewart, 2015; Stewart & Zack, 2008) and the current study (α = .78).

Alcohol and drug use

Alcohol and drug use were measured using single items developed by the funding body of the gambling service, the Victorian Responsible Gambling Foundation: How would you describe your alcohol consumption over the past fortnight? (alcohol use) and How would you describe your use of illicit drugs over the past fortnight? (drug use). Participants answered each of these items using the response options of none, occasional, moderate, heavy, and excessive.

Gambling-related legal consequences

Gambling-related legal consequences were measured using a single item: Do you have any current or impending court or legal matters related to gambling? A dichotomous response option was employed (yes/no).

Work and social adjustment

Work and social adjustment was measured using the five-item Work and Social Adjustment Scale (WSAS: Mundt, Marks, Shear, & Greist, 2002). The WSAS is designed to assess the degree to which individuals with a specific identified disorder (e.g., gambling disorder) believe they have been functionally impaired by their condition across a range of domains (work, home, leisure, and social and personal relationships) using an 8-point scale ranging from 0 (no impairment) to 8 (very severe impairment). The WSAS has displayed good internal consistency in previous research (Brown et al., 2016; Mundt et al., 2002) and in the current study (α = .87).

Impulsivity

The five-item Motor Impulsivity subscale of the Barratt Impulsiveness Scale Short Form (BIS-15: Spinella, 2007) was employed to measure impulsivity. Each item is scored on a 4-point Likert-type scale from 1 (rarely/not at all) to 4 (almost always/always). This measure has been shown to have test–retest reliability (r = .80), as well as good internal consistency in previous research (Brown et al., 2016; Orozco-Cabal, Rodriguez, Herin, Gempeler, & Uribe, 2010; Waluk, Youssef, & Dowling, 2016) and in the current study (α = .82).

Procedure

This study was approved by the University of Melbourne’s Human Ethics Committee (approval no. 0830146.2). Participants were surveyed as part of the pretreatment screening at a gambling counseling service in metropolitan Melbourne, Australia, between August 2009 and January 2011. As per standard practice, all participants were requested to arrive early to their first treatment session at the service to complete the standard pretreatment assessment, into which the modified HITS family violence items were embedded. This paper-based survey was provided to participants by the clinical receptionist upon arrival, and participants were required to return the survey to the receptionist or their clinician during the first session. The response rate was very good with 94% of possible respondents completing the survey. Participants were free to withdraw at any time and were informed that their treatment with the service would not be jeopardized should they refuse to complete the questionnaire.

Data Analysis

SPSS (v.22) was used for data cleaning, and all other analyses were conducted in Stata (v.14) and R Studio (v.0.99.896). Missing data ranged from 10.6% to 26.2% and based on Little’s (1988) missing completely random (MCAR) analysis, the pattern of missingness was deemed to be MCAR (χ² = 3,566.77, df = 3,546, p = .40). Pairwise deletion was applied to cases with more than 30% of any scale missing, and single imputation using Estimation Maximization was used for cases with less than 30% missing. Although several variables were positively skewed, transformations did not improve normality, so a robust variance estimator was used for all inferential tests.

A series of univariate logistic regressions were carried out to assess whether the hypothesized factors (K6 psychological distress, PC-PTSD symptoms of PTSD, GMQ gambling coping motives, alcohol use, drug use, gambling-related legal consequences, WSAS work and social adjustment, BIS impulsivity, and gender) predicted family violence victimization and family violence perpetration.

In the absence of longitudinal or event-level data on the temporal nature of the relationship between problem gambling and family violence, this study regressed each family violence outcome variable (victimization and perpetration) onto gambling symptom severity based on the early evidence from retrospective accounts suggesting that problem gambling generally precedes, or coincides with, both family violence victimization and perpetration (Suomi et al., 2019; Suomi et al., 2013). The degree to which each of the hypothesized factors moderated the relationships between gambling symptom severity and family violence were conducted through a series of binary logistic regressions, where each set of predictors and associated interactions were simultaneously entered into the regression model, followed by simple slopes analysis when an interaction term was found to be significant.

Results

The prevalence of modified HITS family violence in the current sample of treatment-seeking gamblers was 25.5%, with 18.4% reporting victimization and 19.1% reporting perpetration. Of the total sample (n = 141), 15 (10.6%) participants identified their parent, 10 (7.1%) their current or ex-partner, five (3.5%) their sibling, and two (1.4%) their child as the perpetrators of violence toward them. Of the total sample (n = 141), 13 (9.2%) participants reported that they had perpetrated violence toward their current or ex-partner, 12 (8.5%) their parent, seven (5.0%) their sibling, and two (1.4%) their child.

Factors Associated With Family Violence

Table 1 displays the factors that predicted modified HITS family violence victimization and perpetration. In this sample of treatment-seeking gamblers, family violence victimization was significantly predicted by K6 psychological distress (odds ratio [OR] = 1.09), PC-PTSD symptoms of PTSD (OR = 1.41), and gambling-related legal consequences (OR = 5.30). In contrast, family violence perpetration was significantly predicted by PGSI gambling symptom severity (OR = 1.11), gambling-related legal consequences (OR = 5.05), and BIS impulsivity (OR = 1.18). The pairwise relationships between all variables using Spearman’s rho correlations are displayed in Table 2.

Table 1.

Series of Binary Logistic Regressions Predicting Family Violence Victimization and Perpetration.

Predictors of HITS Family Violence	OR	Robust SE	p	95% CIs
DV: HITS family violence victimization
PGSI gambling symptom severity	1.09	0.05	.09	[0.98, 1.19]
Gambling time spent	1.01	0.02	.52	[0.97, 1.05]
Gambling frequency	1.04	0.04	.41	[0.95, 1.12]
Gambling expenditure	1.00	0.00	.92	[0.99, 1.00]
K6 psychological distress	1.09	0.04	.02	[1.01, 1.17]
PC-PTSD symptoms of PTSD	1.41	0.23	.04	[1.02, 1.94]
GMQ gambling coping motives	1.10	0.06	.09	[0.99, 1.23]
Alcohol use	0.86	0.19	.50	[0.57, 1.32]
Drug use	0.83	0.46	.74	[0.28, 2.49]
Gambling-related legal consequences	5.30	3.33	.01	[1.54, 18.18]
WSAS work and social adjustment	1.02	0.02	.37	[0.98, 1.07]
BIS impulsivity	1.04	0.07	.59	[0.91, 1.18]
Gender	2.20	1.00	.08	[0.90, 5.36]
DV: HITS family violence perpetration
PGSI gambling symptom severity	1.11	0.05	.01	[1.03, 1.21]
Gambling time spent	1.00	0.02	.69	[0.97, 1.05]
Gambling frequency	0.99	0.04	.90	[0.91, 1.09]
Gambling expenditure	1.00	0.00	.77	[0.99, 1.00]
K6 psychological distress	1.05	0.04	.15	[0.98, 1.13]
PC-PTSD symptoms of PTSD	1.12	0.18	.45	[0.83, 1.53]
GMQ gambling coping motives	1.01	0.05	.80	[0.92, 1.12]
Alcohol use	0.93	0.20	.76	[0.61, 1.43]
Drug use	0.55	0.30	.27	[0.20, 1.57]
Gambling-related legal consequences	5.05	3.17	.01	[1.48, 17.25]
WSAS work and social adjustment	1.00	0.02	.73	[0.97, 1.05]
BIS impulsivity	1.18	0.08	.01	[1.04, 1.35]
Gender	1.10	0.52	.84	[0.44, 2.78]

Note. HITS = Hurt–Insult–Threaten–Scream; DV = dependent variable; OR = odds ratio; CI = confidence interval; PGSI = Problem Gambling Severity Index; PC-PTSD = Primary Care–Post-Traumatic Stress Disorder; GMQ = Gambling Motivation Questionnaire; WSAS = Work and Social Adjustment Scale; BIS = Barratt Impulsiveness Scale.

Table 2.

Pairwise Relationships Between Family Violence, Gambling Indices, and Hypothesized Moderators.

	1	2	3	4	5	6	7	8	9	10	11	12	13	14
1. HITS family violence victimization
2. HITS family violence perpetration	.56**
3. PGSI gambling symptom severity	.19*	.20*
4. Gambling time spent	.09	.07	.22*
5. Gambling frequency	.14	.05	.05	.35**
6. Gambling expenditure	.04	.08	.09	.38**	.17
7. K6 psychological distress	.17	.11	.52**	.34**	.16	.18*
8. PC-PTSD symptoms of PTSD	.19*	.06	.28**	.13	−.06	.03	.48**
9. GMQ gambling coping motives	.14	.03	.39**	.09	−.07	.12	.41**	.27**
10. Alcohol use	−.06	−.04	.14	.12	.15	.17	.10	.05	.01
11. Drug use	−.04	−.06	.04	−.02	−.02	−.01	.05	.10	−.05	.16
12. Gambling-related legal consequences	.25**	.24**	.13	.10	−.05	.06	.10	.18*	.06	.01	.12
13. WSAS work and social adjustment	.09	.04	.49**	.22*	.11	.06	.54**	.33**	.34**	.15	.07	.14
14. BIS impulsivity	.02	.22*	.34**	.13	−.04	.04	.29**	.29**	.33**	.23*	.13	.15	.36**
15. Gender	.15	.02	.14	−.15	−.17	−.00	.17*	.11	.25*	−.11	−.12	−.03	−.13	−.02

Note. HITS = Hurt–Insult–Threaten–Scream; PGSI = Problem Gambling Severity Index; PC-PTSD = Primary Care–Post-Traumatic Stress Disorder; GMQ = Gambling Motivation Questionnaire; WSAS = Work and Social Adjustment Scale; BIS = Barratt Impulsiveness Scale.

p < .05, **p < .01.

Moderators of the Relationship Between Problem Gambling and Family Violence

In a series of binary logistic regressions, K6 psychological distress, PC-PTSD symptoms of PTSD, GMQ gambling coping motives, alcohol use, drug use, gambling-related legal consequences, WSAS work and social adjustment, BIS impulsivity, and gender were explored as potential moderators on the relationship between PGSI gambling symptom severity and modified HITS family violence. Among these moderated regressions, several significant interaction effects were found only for victimization (see Table 3). These effects were explored further through simple slopes analysis.

Table 3.

Interaction Effects on Family Violence Victimization.

Interaction Term	Odds Ratio	Robust SE	p	95% CIs
DV: HITS family violence victimization
PGSI Gambling Symptom Severity × GMQ Gambling Coping Motives	0.95	0.02	.01	[0.92, 0.99]
PGSI Gambling Symptom Severity × Alcohol Use	1.13	0.05	.02	[1.02, 1.23]

Note. CI = confidence interval; DV = dependent variable; HITS = Hurt–Insult–Threaten–Scream; PGSI = Problem Gambling Severity Index; GMQ = Gambling Motivation Questionnaire.

These analyses revealed that the association between PGSI gambling symptom severity and modified HITS family violence victimization was significant only at low levels of GMQ gambling coping motives (OR = 1.31, 95% confidence interval (CI) [1.08, 1.58], p = .01; Figure 1a). When comparing slopes across different levels of alcohol use, the relationship between PGSI gambling symptom severity and modified HITS family violence victimization was significant for those with moderate (OR = 1.16, 95% CI [1.05, 1.28], p < .01) and high levels (OR = 1.31, 95% CI [1.09, 1.58], p < .01) of alcohol use (Figure 1b).

Figure 1.

Significant interaction effects of PGSI gambling symptom severity and psychosocial characteristics in predicting HITS family violence victimization.

Discussion

Given the limited evidence base relating to the relationship between problem gambling and violence that extends into the family beyond intimate partners, the primary aim of this study was to identify the factors that predicted family violence (physical hurt, insults, threats of harm, and screaming) in a sample of gamblers seeking treatment. The secondary aim was to explore the degree to which these factors moderate the relationship between gambling symptom severity and family violence.

Family Violence Victimization in Problem Gamblers

The prevalence of family violence victimization in the current sample of treatment-seeking gamblers was 18.4%. While this estimate is at the lower end of the range obtained previously in nonrepresentative samples (Dowling, Jackson, et al., 2014; Dowling, Rodda, et al., 2014; Palmer du Preez et al., 2018; Raylu & Oei, 2009), it is consistent with previous studies of family violence among treatment-seeking gamblers who have employed current measures of physical and psychological abuse (Dowling, Jackson, et al., 2014; Raylu & Oei, 2009). Consistent with previous findings from the larger study (Dowling et al., 2018; Dowling, Jackson, et al., 2014; Suomi et al., 2019; Suomi et al., 2013), parents and intimate partners were the most likely to be perpetrators of violence toward problem gamblers, suggesting that these family members are important in understanding the nature of the relationship between problem gambling and family violence.

All of the gambling indices (gambling symptom severity, gambling time spent, gambling frequency, or gambling expenditure) failed to predict family violence victimization. This was not unexpected, given that treatment-seeking gambling samples inherently comprise a restricted range of gambling symptom severity (Dowling, Suomi, Jackson, Lavis, Patford, et al., 2016). Accordingly, several previous studies of treatment-seeking gamblers have failed to find significant associations between gambling symptom severity and physical, psychological, and sexual family violence victimization (Korman et al., 2008; Raylu & Oei, 2009). The purpose of the current study, however, was to explore the factors associated with family violence in this treatment-seeking gambling sample. Psychological distress, symptoms of PTSD, and gambling-related legal consequences significantly predicted family violence victimization. Moreover, the association between gambling symptom severity and victimization was significant only for gamblers with low levels of gambling coping motives and moderate or high levels of alcohol use. The implication of these factors is consistent with different theoretical perspectives on the temporal nature of the relationship between problem gambling and family violence that have been hypothesized by researchers.

For example, the implication of psychological distress and symptoms of PTSD in the victimization experiences of problem gamblers is consistent with the commonly held individual coping perspective that some people employ gambling as a mechanism to physically or emotionally escape family violence victimization experiences (Afifi et al., 2010; Cunningham-Williams et al., 2007; Dowling, Suomi, Jackson, Lavis, Patford, et al., 2016; Echeburua et al., 2011; Korman et al., 2008). However, psychological distress did not significantly moderate the relationship between gambling symptom severity and family violence victimization. Moreover, this theoretical conceptualization implicates gambling coping motives and gender; but the association between gambling symptom severity and family violence victimization was significant only at low levels of gambling coping motives; and gender failed to be a significant moderator of the relationship.

Similarly, the implication of gambling-related legal consequences in the victimization experiences of problem gamblers is consistent with the hypothesis put forward by researchers that legal problems resulting from gambling result in chronic family stress, domestic conflict, and the perpetration of violence by family members toward the gambler (Dowling, Suomi, Jackson, Lavis, Patford, et al., 2016; Echeburua et al., 2011; Korman et al., 2008).

Although alcohol and drug use did not predict family violence victimization, the relationship between gambling symptom severity and family violence victimization was moderated by alcohol use, whereby there was a significant association only for those with moderate and high levels of alcohol use. This result is consistent with findings from previous community research that hazardous alcohol use by moderate-risk/problem gamblers exacerbates the risk for the victimization of violence by family members toward gamblers (Dowling et al., 2018). This result is not unexpected given the central role alcohol consumption plays in shaping the extent and impact of gambling behavior and IPV (Devries et al., 2014; Dowling et al., 2015; Dowling et al., 2017; World Health Organization, 2006). For example, alcohol use may increase the likelihood of gambling via reduced control, exacerbate gambling losses and related consequences, reduce capability to negotiate a nonviolent resolution, and exacerbate other family stressors (Devries et al., 2014; World Health Organization, 2006).

Although this study implicates psychological distress, PTSD symptoms, gambling-related legal consequences, gambling coping motives, and alcohol use in the relationship between problem gambling and family violence victimization, the cross-sectional data from this study cannot support the causal or temporal hypotheses that have been put forward by researchers. It is evident that longitudinal or event-level research is required to establish the role of these factors in the relationship between problem gambling and family violence victimization.

Family Violence Perpetration in Problem Gambling

The prevalence of family violence perpetration in the current sample of treatment-seeking gamblers was 19.1%, which is also at the lower end of the range obtained previously in nonrepresentative samples (Dowling, Jackson, et al., 2014; Dowling, Rodda, et al., 2014; Kausch et al., 2006; Palmer du Preez et al., 2018; Raylu & Oei, 2009). Like victimization, intimate partners and parents were the most likely to be perpetrators of violence, again suggesting that family violence in problem gambling families is maintained within the immediate family. Although most indices of gambling (gambling time spent, gambling frequency, or gambling expenditure) failed to predict family violence perpetration, perpetration was significantly predicted by gambling symptom severity. Although this significant relationship was not necessarily expected, it provides additional support that there is a significant association between problem gambling and family violence perpetration, even in a sample in which there is a restricted range of gambling symptom severity scores (Dowling, Suomi, Jackson, Lavis, Patford, et al., 2016). Family violence perpetration was also significantly predicted by gambling-related legal consequences and impulsivity. The higher rate of gambling-related legal consequences in problem gamblers reporting family violence perpetration is consistent with the hypothesis put forward by researchers that legal problems resulting from gambling create considerable stress for the gambler, resulting in the perpetration of violence toward family members (Afifi et al., 2010; Dowling, Suomi, Jackson, Lavis, Patford, et al., 2016; Korman et al., 2008; Muelleman et al., 2002). The significant finding in relation to impulsivity, which is consistent with previous research relating to IPV perpetration (physical, psychological, and sexual) in male batterers (Brasfield et al., 2012), is also consistent with the proposition that it may serve as a common underlying third factor that leads to a greater risk for problem gambling and family violence perpetration (Brasfield et al., 2012; Korman et al., 2008).

However, consistent with previous research in a community study (Dowling et al., 2018), none of the comorbidity variables significantly moderated the relationships between problem gambling and family violence perpetration. There may, however, be any number of potential relationships between these comorbidities, gambling behavior, and family violence perpetration. Alternatively, they may be associated with only some types of violence; or their moderating effect may have been diluted by the measurement of violence involving non-intimate partner family members. Again, further longitudinal or event-level research is required to elucidate the proximal relationships between these variables.

Study Limitations

Limitations of this study include the cross-sectional design, the use of a sample-seeking treatment for problem gambling, and a relatively small sample. As previously indicated, the cross-sectional design does not allow for inferences regarding causal associations among variables. Treatment-seeking samples may not be representative of problem gamblers in the community and may not allow the relationship between the problem behaviors to be explored across the full spectrum of problem-gambling severity. Based on a priori calculation (N > 50 + 8m, where m is the number of independent variables; Tabachnick & Fidell, 2013), the current study was aiming for a sample size of 154; however, it fell just short of recruiting that sample size. Regardless, the findings from this treatment-seeking sample are very comparable to a similar study conducted in a population-representative community study (Dowling et al., 2018), allowing for the triangulation of findings from different research methodologies.

This study is also limited by the use of brief measures of family violence victimization and perpetration and the variable measurement time frames of the measures employed in this study. The HITS (Sherin et al., 1998) was employed and converted to a perpetration version because there are currently no very brief standardized screening instruments for both family violence victimization or perpetration (Rabin et al., 2009). However, the modified HITS scale items (Sherin et al., 1998) fail to differentiate between violence types; do not measure the frequency of violence; measure purely acontextual acts of family violence; exclude some elements of family violence such as financial, sexual, and neglectful harm; and have unknown classification accuracy.

Implications for Researchers

The limitations of this study suggest that longitudinal studies and event-level analyses of community samples are needed to determine the proximal relationships between problem gambling and family violence, as well as the degree to which factors such as psychiatric distress, PTSD symptoms, and gambling-related legal consequences are underlying causal mechanisms. Moreover, the development of standardized brief instruments and the use of measures with consistent time frames will be important in improving the methodologies adopted in future studies addressing this important area of research.

Implications for Clinicians

Despite these limitations, the current study enhanced our understanding of the factors associated with the relationship between problem gambling and family violence and the factors that magnify the strength of the relationship. The findings provide further support for routine screening of family violence in problem gambling services and of problem gambling in IPV services (Dowling, Suomi, Jackson, Lavis, Patford, et al., 2016; Echeburua et al., 2011; Korman et al., 2008). They also highlight the need for prevention and intervention programs to lower the risk of the co-occurrence of these problem behaviors (Dowling, Suomi, Jackson, Lavis, Patford, et al., 2016). The findings of this study suggest that strategies to manage psychological distress, PTSD symptoms, and alcohol use are potentially important targets for prevention and intervention efforts addressing family violence victimization; while strategies to manage impulsivity are potentially important targets for prevention and intervention efforts addressing the perpetration of family violence (Afifi et al., 2010; Korman et al., 2008). Finally, it is also evident that people who report legal problems or have impending legal matters resulting from their gambling should be screened in both the service delivery system and court system for both family violence victimization and perpetration.

Conclusion

The current study enhanced our understanding of the violence that extends beyond intimate partners by revealing some of the factors that are implicated in the relationship between problem gambling and family violence (Dowling, Jackson, et al., 2014). In this sample of treatment-seeking gamblers, the prevalence of family violence was 18.4% for victimization, 19.1% for perpetration, and 25.5% for either victimization or perpetration. Psychological distress, PTSD symptoms, and gambling-related consequences significantly predicted family violence victimization; and the relationship between gambling symptom severity and victimization was significant only for gamblers with low levels of gambling coping motives and moderate or high levels of alcohol use. In contrast, gambling symptom severity, gambling-related legal consequences, and impulsivity significantly predicted the perpetration of family violence, but none of the factors under investigation significantly moderated the relationship between gambling symptom severity and family violence perpetration. These findings can inform future screening, prevention, and intervention efforts designed to lower the co-occurrence of problem gambling and family violence (Dowling, Suomi, Jackson, Lavis, Patford, et al., 2016).

Footnotes

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: Over the past 3 years, N.D., A.S., S.M., and A.J. have received funding from multiple sources, including government departments (some through hypothecated taxes from gambling revenue). N.D. and S.M. have also received funding from the Victorian Responsible Gambling Foundation (through hypothecated taxes from gambling revenue), as well as the National Association for Gambling Studies (NAGS), a not-for-profit organization with individual members across all stakeholder groups, which derives its funding from member fees and conference proceeds. S.M. has formerly been the Victorian state representative (unpaid) on the NAGS Executive Committee. None of the authors have knowingly received research funding from the gambling industry or any industry-sponsored organization.

ORCID iD

Nicki A. Dowling

Author Biographies

Nicki A. Dowling is an associate professor in the School of Psychology at Deakin University, with an honorary position as Principal Research Fellow in the Melbourne Graduate School of Education at the University of Melbourne. She is a registered clinical psychologist with significant experience in the treatment of problem gamblers in her part-time employment as a problem gambling counselor (2003-2013).

Erin Oldenhof is a doctor of psychology (clinical) candidate, who has worked clinically in the AOD (alcohol and other drug) sector for a number of years. Her research interests extend to both behavioral and substance addictions, and she has produced a number of publications on problem gambling.

Sue Cockman is an educational and developmental psychologist in private practice with treatment interests in the areas of depression, anxiety, panic, self-harm, addiction, and sleep disorders in adults and children.

Aino Suomi is a clinically trained psychologist, currently working in research on a range of vulnerable populations with a specific family focus. She has published on family violence and gambling, family impacts of addictions and multiple mental health conditions as well as family treatments for post-traumatic stress disorder.

Stephanie S. Merkouris, PhD, is a research fellow in the School of Psychology at Deakin University. Her research interests include the prospective examination of factors associated with gambling problems and treatment outcomes.

Alun C. Jackson is a director of the Australian Centre for Heart Health, and was formerly director of the Problem Gambling Research and Treatment Centre at the University of Melbourne where he conducted studies on problem gambling with relation to, among other things, service design and treatment effectiveness; family violence; children and adolescents; and intergenerational transmission.

References

Afifi

T. O.

Brownridge

D. A.

MacMillan

Sareen

(2010). The relationship of gambling to intimate partner violence and child maltreatment in a nationally representative sample. Journal of Psychiatric Research, 44, 331-337. doi:10.1016/j.jpsychires.2009.07.010

American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Arlington, VA: American Psychiatric Publishing.

Brasfield

Febres

Shorey

Strong

Ninnemann

Elmquist

. . . Stuart

G. L.

(2012). Male batterers’ alcohol use and gambling behavior. Journal of Gambling Studies, 28, 77-88. doi:10.1007/s10899-011-9246-0

Brasfield

Shorey

Febres

Strong

Stuart

G. L.

(2011). Hazardous gambling among women court-mandated to batterer intervention programs. American Journal on Addictions, 20, 176-177. doi:10.1111/j.1521-0391.2010.00103.x

Brown

Oldenhof

Allen

Dowling

(2016). An empirical study of personality disorders among treatment-seeking problem gamblers. Journal of Gambling Studies, 32, 1079-1100. doi:10.1007/s10899-016-9600-3

Chan

E. M. L.

Dowling

N. A.

Jackson

A. C.

Shek

D. T. S.

(2016). Gambling related family coping and the impact of problem gambling on families in Hong Kong. Asian Journal of Gambling Issues and Public Health, 6(1), 1. doi:10.1186/s40405-016-0009-9

Cunningham-Williams

R. M.

Abdallah

A. B.

Callahan

Cottler

(2007). Problem gambling and violence among community-recruited female substance abusers. Psychology of Addictive Behaviors, 21, 239-243. doi:10.1037/0893-164x.21.2.239

Devries

K. M.

Child

J. C.

Bacchus

L. J.

Mak

Falder

Graham

. . . Heise

(2014). Intimate partner violence victimization and alcohol consumption in women: A systematic review and meta-analysis. Addiction, 109, 379-391. doi:10.1111/add.12393

Dowling

N. A.

Cowlishaw

Jackson

A. C.

Merkouris

S. S.

Francis

K. L.

Christensen

D. R.

(2015). Prevalence of psychiatric co-morbidity in treatment-seeking problem gamblers: A systematic review and meta-analysis. Australian & New Zealand Journal of Psychiatry, 49, 519-539. doi:10.1177/0004867415575774

10.

Dowling

N. A.

Ewin

Youssef

G. J.

Suomi

Thomas

S. A.

Merkouris

S. S.

Jackson

A. C.

(2018). Problem gambling and family violence: Findings from a nationally representative study. Journal of Behavioral Addictions, 7, 806-813. doi:10.1556/2006.7.2018.74

11.

Dowling

N. A.

Jackson

A. C.

Suomi

Lavis

Thomas

S. A.

Patford

. . . Bellringer

M. E.

(2014). Problem gambling and family violence: Prevalence and patterns in treatment-seekers. Addictive Behaviors, 39, 1713-1717. doi:10.1016/j.addbeh.2014.07.006

12.

Dowling

N. A.

Merkouris

S. S.

Greenwood

C. J.

Oldenhof

Toumbourou

J. W.

Youssef

G. J.

(2017). Early risk and protective factors for problem gambling: A systematic review and meta-analysis of longitudinal studies. Clinical Psychology Review, 51, 109-124. doi:10.1016/j.cpr.2016.10.008

13.

Dowling

N. A.

Rodda

S. N.

Lubman

D. I.

Jackson

A. C.

(2014). The impacts of problem gambling on concerned significant others accessing web-based counselling. Addictive Behaviors, 39, 1253-1257. doi:10.1016/j.addbeh.2014.04.011

14.

Dowling

N. A.

Smith

Thomas

(2009). The family functioning of female pathological gamblers. International Journal of Mental Health and Addiction, 7, 29-44. doi:10.1007/s11469-007-9126-0

15.

Dowling

N. A.

Suomi

Jackson

A. C.

Lavis

(2016). Problem gambling family impacts: Development of the Problem Gambling Family Impact Scale. Journal of Gambling Studies, 32, 935-955. doi:10.1007/s10899-015-9582-6

16.

Dowling

N. A.

Suomi

Jackson

A. C.

Lavis

Patford

Cockman

. . . Abbott

(2016). Problem gambling and intimate partner violence: A systematic review and meta-analysis. Trauma, Violence, & Abuse, 17, 43-61. doi:10.1177/1524838014561269

17.

Dowling

N. A.

Youssef

Jackson

A. C.

Pennay

Francis

K. L.

Pennay

Lubman

D. I.

(2016). National estimates of Australian gambling prevalence: Findings from a dual-frame omnibus survey. Addiction, 111, 420-435. doi:10.1111/add.13176

18.

Echeburua

Gonzalez-Ortega

de Corral

Polo-Lopez

(2011). Clinical gender differences among adult pathological gamblers seeking treatment. Journal of Gambling Studies, 27, 215-227. doi:10.1007/s10899-010-9205-1

19.

Ferris

Wynne

(2001). The Canadian problem gambling index: Final report. Ottawa, Ontario: Canadian Centre on Substance Abuse.

20.

Foa

E. B.

Riggs

D. S.

Gershuny

B. S.

(1995). Arousal, numbing, and intrusion: Symptom structure of PTSD following assault. American Journal of Psychiatry, 152, 116-120. doi:10.1176/ajp.152.1.116

21.

Goldstein

A. L.

Walton

M. A.

Cunningham

R. M.

Resko

S. M.

Duan

(2009). Correlates of gambling among youth in an inner-city emergency department. Psychology of Addictive Behaviors, 23, 113-121. doi:10.1037/a0013912

22.

Goodwin

B. C.

Browne

Rockloff

Rose

(2017). A typical problem gambler affects six others. International Gambling Studies, 17, 276-289. doi:10.1080/14459795.2017.1331252

23.

Kausch

Rugle

Rowland

D. Y.

(2006). Lifetime histories of trauma among pathological gamblers. American Journal on Addictions, 15, 35-43. doi:10.1080/10550490500419045

24.

Kessler

R. C.

Andrews

Colpe

L. J.

Hiripi

Mroczek

D. K.

Normand

S. L.

. . . Zaslavsky

A. M.

(2002). Short screening scales to monitor population prevalences and trends in non-specific psychological distress. Psychological Medicine, 32, 959-976. doi:10.1017/S0033291702006074

25.

Korman

Collins

Dutton

Dhayanandhan

Littman-Sharp

Skinner

W. J. W.

(2008). Problem gambling and intimate partner violence. Journal of Gambling Studies, 24, 13-23. doi:10.1007/s10899-007-9077-1

26.

Lambe

Mackinnon

S. P.

Stewart

S. H.

(2015). Validation of the gambling motives questionnaire in emerging adults. Journal of Gambling Studies, 31, 867-885. doi:10.1007/s10899-014-9467-0

27.

Langham

Thorne

Browne

Donaldson

Rose

Rockloff

(2016). Understanding gambling related harm: A proposed definition, conceptual framework, and taxonomy of harms. BMC Public Health, 16(1), Article 80. doi:10.1186/s12889-016-2747-0

28.

Little

R. J. A.

(1988). A test of missing completely at random for multivariate data with missing values. Journal of the American Statistical Association, 83, 1198-1202. doi:10.1080/01621459.1988.10478722

29.

Muelleman

R. L.

DenOtter

Wadman

M. C.

Tran

T. P.

Anderson

(2002). Problem gambling in the partner of the emergency department patient as a risk factor for intimate partner violence. Journal of Emergency Medicine, 23, 307-312. doi:10.1016/S0736-4679(02)00543-7

30.

Mundt

J. C.

Marks

I. M.

Shear

M. K.

Greist

J. H.

(2002). The Work and Social Adjustment Scale: A simple measure of impairment in functioning. British Journal of Psychiatry, 180, 461-464. doi:10.1192/bjp.180.5.461P

31.

Neal

P. N.

Delfabbro

P. H.

O’Neil

M. G.

(2005). Problem gambling and harm: Towards a national definition. Melbourne, Australia: Office of Gaming and Racing and Department of Justice.

32.

Orford

Copello

Velleman

Templeton

(2010). Family members affected by a close relative’s addiction: The stress-strain-coping-support model. Drugs: Education, Prevention and Policy, 17(Suppl. 1), 36-43. doi:10.3109/09687637.2010.514801

33.

Orozco-Cabal

Rodriguez

Herin

D. V.

Gempeler

Uribe

(2010). Validity and reliability of the Abbreviated Barratt Impulsiveness Scale in Spanish (BIS-15S). Revista Colombiana de Psiquiatría, 39, 93-109. doi:10.1016/S0034-7450(14)60239-0

34.

Palmer

Preez

Bellringer

Pearson

Dowling

Suomi

Koziol-Mclain

. . . Jackson

(2018). Family violence in gambling help-seeking populations. International Gambling Studies, 18, 477-494. doi:10.1080/14459795.2018.1480648

35.

Prins

Ouimette

Kimerling

Cameron

R. P.

Hugelshofer

D. S.

Shaw-Hegwer

. . . Sheikh

(2004). The primary care PTSD screen (PC-PTSD): Development and operating characteristics. Primary Care Psychiatry, 9(1), 9-14, doi:10.1185/135525703125002360

36.

Rabin

R. F.

Jennings

J. M.

Campbell

J. C.

Bair-Merritt

M. H.

(2009). Intimate partner violence screening tools. American Journal of Preventive Medicine, 36(5), 439-445.e434. doi:10.1016/j.amepre.2009.01.024

37.

Raylu

Oei

T. P.

(2009). Factors associated with the severity of gambling problems in a community gambling treatment agency. International Journal of Mental Health and Addiction, 7, 124-137. doi:10.1007/s11469-008-9160-6

38.

Roberts

Coid

King

Murphy

Turner

Bowden-Jones

. . . Landon

(2016). Gambling and violence in a nationally representative sample of UK men. Addiction, 111, 2196-2207. doi:10.1111/add.13522

39.

Roberts

Sharman

Coid

Murphy

Bowden-Jones

Cowlishaw

Landon

(2017). Gambling and negative life events in a nationally representative sample of UK men. Addictive Behaviors, 75, 95-102. doi:10.1016/j.addbeh.2017.07.002

40.

Schluter

P. J.

Abbott

M. W.

Bellringer

M. E.

(2008). Problem gambling related to intimate partner violence: Findings from the Pacific Islands families study. International Gambling Studies, 8, 49-61. doi:10.1080/14459790701870134

41.

Sherin

K. M.

Sinacore

J. M.

X. Q.

Zitter

R. E.

Shakil

(1998). HITS: A short domestic violence screening tool for use in a family practice setting. Family Medicine, 30, 508-512.

42.

Spinella

(2007). Normative data and a short form of the Barratt Impulsiveness Scale. International Journal of Neuroscience, 117, 359-368. doi:10.1080/00207450600588881

43.

Stewart

S. H.

Zack

(2008). Development and psychometric evaluation of a three-dimensional Gambling Motives Questionnaire. Addiction, 103, 1110-1117. doi:10.1111/j.1360-0443.2008.02235.x

44.

Suomi

Dowling

N. A.

Thomas

Abbott

Bellringer

Battersby

. . . Jackson

A. C.

(2019). Patterns of family and intimate partner violence in problem gamblers. Journal of Gambling Studies, 35(2), 465-484. doi:10.1007/s10899-018-9768-9

45.

Suomi

Jackson

A. C.

Dowling

N. A.

Lavis

Patford

Thomas

S. A.

. . . Cockman

(2013). Problem gambling and family violence: Family member reports of prevalence, family impacts and family coping. Asian Journal of Gambling Issues and Public Health, 3(1), 13. doi:10.1186/2195-3007-3-13

46.

Tabachnick

B. G.

Fidell

L. S.

(2013). Using multivariate statistics (6th ed.). Boston: Pearson.

47.

Thompson

M. P.

Basile

K. C.

Hertz

M. F.

Sitterle

(2006). Measuring intimate partner violence victimization and perpetration: A compendium of assessment tools. Atlanta, GA: Centre for Disease Control and Prevention.

48.

Victorian Department of Human Services. (2012). Assessing children and young people experiencing family violence: A practice guide for family violence practitioners. Melbourne, Australia: Author.

49.

Waluk

Youssef

Dowling

(2016). The relationship between problem gambling and attention deficit hyperactivity disorder. Journal of Gambling Studies, 32, 591-604. doi:10.1007/s10899-015-9564-8

50.

Williams

R. J.

Volberg

Stevens

R. M.

(2012). The population prevalence of problem gambling: Methodological influences, standardized rates, jurisdictional differences, and worldwide trends. Toronto, Canada: Ontario Problem Gambling Research Centre & Ontario Ministry of Health and Long Term Care.

51.

World Health Organization. (2006). Intimate partner violence and alcohol fact sheet. Geneva, Switzerland: Author.

52.

World Health Organization. (2013). Responding to intimate partner violence and sexual violence against women: WHO clinical and policy guidelines. Geneva, Switzerland: Author.