# Childhood trauma, complex PTSD, and severity of online sports betting in French bettors

Maeva D'agostino, Samantha Tessier, Oulmann Zerhouni, Lucia Romo

► To cite this version:

Maeva D'agostino, Samantha Tessier, Oulmann Zerhouni, Lucia Romo. Childhood trauma, complex PTSD, and severity of online sports betting in French bettors. European Journal of Trauma and Dissociation, 2025, 9 (4), pp.100602. 10.1016/j.ejtd.2025.100602. hal-05355558

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Research Paper

# Childhood trauma, complex PTSD, and severity of online sports betting in French bettors

<figure><img src="image_2.png" /></figure>

Maeva d'Agostino<sup>a</sup>, Samantha Tessier<sup>a</sup>, Oulmann Zerhouni<sup>b,c,*</sup>, Lucia Romo<sup>a,d,e ◊</sup>

## ARTICLE INFO

**Keywords:**

- Trauma
- Problem gambling
- France
- Internet gambling

## ABSTRACT

**Background:** Online sports betting has surged in France, creating significant public health and clinical issues. Although childhood trauma and PTSD are known risk factors for gambling disorder, their role in the context of addiction—especially with regard to online sports betting—has not been well-examined

**Objective:** Determine how five Childhood Trauma Questionnaire (CTQ) subscales and International Trauma Questionnaire (ITQ) symptom severity are associated with gambling severity (GMQ-F) among French sports bettors and derive actionable insights for addiction interventions

**Methods:** We conducted a cross-sectional survey of 135 adult French online sports bettors. Participants completed the CTQ, ITQ, GMQ-F, and the MIH5 impulsivity scale. Two hierarchical regressions modeled gambling severity: Step 1 included CTQ subscales, and Step 2 included the ITQ total score and CTQ × ITQ interactions. Covariates were age, gender, and impulsivity. Prevalence was as follows (valid n = 134 for CTQ): emotional abuse 44.03 % (59/134), sexual abuse 98.51 % (132/134), physical neglect 88.81 % (119/134), and physical abuse 39.55 % (53/134). All participants met the 'problematic' threshold (100 %, n = 135) on the French CPGI

**Results:** Physical abuse and overall PTSD symptoms independently were associated with higher betting severity. Unexpectedly, sexual abuse showed a negative association, warranting further exploration. No significant trauma × PTSD interactions were found

**Conclusions:** PTSD symptoms and childhood physical abuse are robust predictors of the severity of online sports betting. Incorporating trauma-informed modules into standard gambling interventions, particularly those targeting arousal regulation and coping, may enhance treatment efficacy. Future addiction research should integrate detailed trauma profiling to refine risk stratification and prevention strategies.

Over the last decade, online sports betting has become a prevalent addictive behavior, exhibiting increasing rates of problematic engagement and substantial socioeconomic costs. Gambling disorder is characterized by loss of control, preoccupation with gambling, and continued gambling despite adverse consequences (APA, 2013). While impulsivity and cognitive biases are well-established drivers of gambling severity, emerging evidence suggests that childhood trauma and post-traumatic stress symptoms significantly amplify addiction risk. Childhood trauma is a significant risk factor for a range of addictive behaviors. Recent meta-analyses and large-scale reviews confirm that individuals exposed to early trauma have elevated odds of developing addictions to substances and behaviors later in life (Roberts et al., 2017).

For example, a comprehensive 2024 meta-analysis found that childhood maltreatment robustly predicts various types of substance misuse in youth (Rakovski et al., 2024). Similar patterns appear in behavioral addictions like gambling. Epidemiological studies reveal that people with gambling disorders disproportionately report traumatic life events and adverse childhood experiences compared to non-gamblers. In a nationally representative UK survey, men with pathological gambling habits were more than twice as likely as non-gamblers to have witnessed domestic violence or suffered physical abuse in childhood (Roberts et al., 2017). Even after controlling for alcohol/drug use, severe gamblers had significantly higher exposure to early and adult trauma, underlining trauma as an independent contributor to gambling

<footnote><sup>a</sup> University Paris Nanterre UR 4430 Departement of Psychology, 200 av de la république 92001 Nanterre Cedex, France</footnote>

<footnote><sup>b</sup> Université de Rouen Normandie, CRFDP, 1 rue Thomas Becket, 76821 Mont-Saint-Aignan Cedex, France</footnote>

<footnote><sup>c</sup> Laboratoire Parisien de Psychologie Sociale, EA 4386 (équipe PS2C), 200 av. de la République 92001 Nanterre Cedex, France</footnote>

<footnote><sup>d</sup> Hôpital Universitaire Raymond-Poincaré, Service de Pathologies Professionnelles (AP-HP) 92380 Garches, France</footnote>

<footnote><sup>e</sup> Inserm CESP 1018 UPS, 114, rue Edouard-Vaillant 94 805 Villejuif Cedex, France</footnote>

<footnote>* Corresponding author.</footnote>

<footnote>E-mail addresses: oulmann.zerhouni@univ-rouen.fr (O. Zerhouni), lromodes@parisnanterre.fr (L. Romo).</footnote>
problems (Roberts et al., 2017). Consistent with these findings, Leppink and Grant (2015) reported that nearly one-quarter (22.6 %) of diagnosed gamblers had experienced at least one traumatic life event. Likewise, Estevez et al. (2023) observed a positive correlation between the number of traumatic events and the intensity of gambling behavior in adolescents and young adults. Taken together, recent evidence – including meta-analytic data – reinforces that trauma exposure confers vulnerability to addictive behaviors broadly, and gambling disorder in particular, by increasing the likelihood and severity of such conditions (Ogińska-Bulik, 2024). Despite the global evidence linking trauma and gambling, a notable gap remains in the research literature: a lack of community-based data from France examining the nuanced "subscale" relationships between trauma and the severity of online gambling. Much of the existing literature on trauma and gambling comes from North America, Oceania, or international meta-analyses, and relatively few studies have focused on French populations. France has a unique gambling landscape — online betting was legalized in 2010, resulting in the rapid growth of internet sports betting and poker platforms. National surveys estimate that approximately 2.7 % of the French population are problem gamblers, a prevalence similar to that of other Western countries. However, these surveys and cohorts (e.g., the "JEU" cohort study) have primarily investigated the demographic and behavioral correlates of gambling, such as age of onset, preferred game type, and comorbid substance use (Guillou-Landreat et al., 2024).

We conducted an observational study to address this critical gap by examining how five distinct dimensions of childhood trauma—measured via the CTQ—and post-traumatic stress symptoms, both simple PTSD and complex PTSD as assessed by the ITQ, uniquely contribute to the severity of online sports betting in a population of adult sports bettors. We use hierarchical regression models to separate the effects of trauma subtypes and PTSD/C-PTSD symptom clusters on gambling severity.

## Trauma and addictive behaviors

The risk of developing an addiction seem to be increased by trauma, and more severe clinical profiles of addiction are associated with it. Individuals with a history of trauma tend to exhibit addictive behavior at an earlier age and experience greater comorbid psychopathology. Among gambling populations, individuals with childhood trauma report engaging in a greater variety of gambling activities and experiencing more intense gambling urges. Many problem gamblers have experienced multiple forms of abuse or neglect — one study found an average of four distinct types of trauma among gambling addicts. These trauma-exposed gamblers often exhibit more severe symptoms of depression, anxiety, and suicidal ideation than their non-traumatized counterparts (Leppink & Grant, 2015). A systematic review by Moore and Grubbs (2021) synthesized 74 studies and concluded that stress, traumatic experiences, and PTSD symptom severity influence the severity of gambling disorder (Moore & Grubbs, 2021). Notably, the timing, type, and frequency of trauma all modulate its impact on gambling severity. For example, childhood traumas (when vulnerability is high) may be especially predictive of later gambling problems. This aligns with the broader literature on addiction showing a "dose-response" relationship between adverse childhood experiences (ACEs) and addictive outcomes — more or earlier trauma confers greater risk. Trauma's effects on addiction are multifaceted. It can be a precipitant of addictive behavior via maladaptive coping, a consequence of addiction (e.g., traumatic outcomes from gambling-related violence or crime), or part of a self-perpetuating cycle (Monson et al., 2023). Qualitative syntheses underscore this complex, bidirectional relationship: Gambling can result from trauma (e.g., financial ruin or victimization) and can also result in trauma. These two factors can reinforce each other cyclically (Monson et al., 2023).

Recent high-level evidence confirms that childhood trauma is a significant risk factor for addictive behaviors, including online sports betting.

While much of the meta-analytic research has centered on substance use or general gambling, the same mechanisms likely apply to internet-based betting. Online gambling participation has surged among young adults in recent years, a demographic that often carries unad dressed childhood adversities (Sohn, 2023). The constant accessibility and rapid feedback of online sports betting may especially attract in- dividuals exposed to trauma seeking distraction or emotional regulation. Thus, trauma history emerges as a key determinant not only of whether someone develops a gambling problem but also of how severe that problem becomes—a relationship documented across diverse studies and now supported by aggregate reviews. While most large-scale re- views have focused on general or land-based gambling, online sports betting shares key addictive features—constant accessibility, rapid feedback, and anonymity—that may appeal to individuals with a history of trauma (Lopez-Gonzalez et al., 2019; Granero et al., 2020). Indeed, young adults, among whom both online betting participation and un- addressed childhood adversities are common, show sharp increases in problem gambling rates (Nyemcsok et al., 2022; Håkansson & Widinghoff, 2020). Therefore, childhood trauma is a pivotal factor in not only whether someone develops a gambling problem but also in determining the severity of the problem, a relationship that is now firmly supported by recent meta-analyses (Moore & Grubbs, 2021; Estevez et al., 2023).

## PTSD vs. C-PTSD: Underlying mechanisms

Post-traumatic stress disorder (PTSD) and complex PTSD (C-PTSD) are two forms of post-trauma psychopathology which may affect gambling behavior differently. PTSD typically arises from a single life-threatening or horrific event. It is defined by four symptom clusters: intrusive re-experiencing, avoidance of reminders, negative alterations in mood and cognition, and hyperarousal. In contrast, C-PTSD results from prolonged or repetitive trauma, often interpersonal trauma in childhood, and includes the core symptoms of PTSD as well as distur bances in self-organization (DSO), namely, pervasive emotion dysregu- lation, a negative self-concept (e.g., shame and worthlessness), and interpersonal difficulties (Rossi et al., 2023). These additional C-PTSD features reflect the profound developmental impact of chronic trauma. Importantly, these features implicate mechanisms, such as deficits in affect regulation, that may heighten vulnerability to addictions. While PTSD may lead to gambling as an acute escape from intrusive memories or hyperarousal ("distraction through gambling"), C-PTSD can reinforce cycles of addiction more powerfully via chronic emotional dysregulation and impaired self-worth.

Emerging evidence supports distinguishing late-adolescent addic- tions from PTSD and found that complex PTSD (C-PTSD) symptom- atology showed stronger associations with behavioral addictions (including gambling) than PTSD symptomatology (Rossi et al., 2023). In their sample, youth meeting criteria for C-PTSD had significantly higher odds of engaging in problematic gambling than those with PTSD alone. Furthermore, C-PTSD symptoms mediated a substantial portion (approximately 59 %) of the effect of trauma exposure on addictive behaviors, far more than standard PTSD symptoms. These findings suggest that the additional self-regulatory impairments associated with C-PTSD may account for much of the impact of trauma on addiction. One key mediator is emotion dysregulation (ED), the inability to manage distressing emotions, which is a hallmark of C-PTSD. Furthermore, ED mediated the link between trauma and multiple addictions. Gambling, especially online betting, can serve as an immediately accessible means to numb or modulate emotions for those with poor regulation skills. The anonymity and convenience of online platforms may reinforce this effect by facilitating dissociation from the consequences of gambling. Indeed, anonymity reduces social stigma and oversight, which trauma survivors may find appealing when attempting to self-soothe through betting. Additionally, this removes protective checks, such as concerned family members, which could exacerbate gambling severity in this population.
Another notable mechanism is dissociation, a psychological escape characterized by detachment from reality and frequently associated with trauma. Pathological dissociation, which includes feeling numb, zoning out, and experiencing trance-like states, appears to link childhood trauma and the severity of gambling disorder. Imperatori et al. (2017) demonstrated that, among casino gamblers, childhood trauma's effect on gambling severity was entirely mediated by dissociative symptoms. This finding aligns with clinical observations that many problem gamblers enter a dissociative "zone" while betting, temporarily escaping painful memories or emotions. Dissociation is often associated with complex trauma and C-PTSD. Many individuals with C-PTSD experience depersonalization or emotional numbing as part of their DSO symptoms. Moore and Grubbs (2021) also emphasized the role of dissociation, reporting that dissociative tendencies in PTSD have a greater impact on gambling disorder severity than trauma exposure itself. Indeed, the severity of PTSD symptoms correlates more strongly with worse gambling outcomes than the mere occurrence of traumatic events. This underscores the importance of trauma-related psychopathology, such as intrusive flashbacks or dissociative avoidance, in driving addictive behavior (Moore & Grubbs, 2021). This finding aligns with clinical data showing that gamblers with active PTSD tend to have more intense and intractable gambling problems. PTSD symptom levels uniquely predict gambling in response to negative emotions (e.g., gambling when depressed or anxious), even when controlling for impulsivity and substance use (Grubbs, Chapman and Shepherd, 2019). PTSD-affected gamblers are more likely to believe that gambling "improves my mood" or "helps me escape," reflecting an emotion-regulation motive.

Complex PTSD involves persistent difficulties with emotion regulation and dissociation that go beyond those seen in standard PTSD. These difficulties intensify the risk and severity of gambling behaviors. Individuals with C-PTSD often gamble to cope with overwhelming emotions and shame, which can lead to more entrenched betting patterns. Because the anonymity and ease of online sports betting facilitate this maladaptive coping mechanism, it is crucial for clinicians to distinguish between PTSD and C-PTSD when assessing gamblers. Trauma-informed interventions that emphasize emotion-regulation training and grounding techniques for dissociation are likely more effective than standard PTSD treatments alone (Grubbs, Chapman & Shepherd, 2019; López-González et al., 2019; Livingstone & Rintoul, 2021; Tsurumi et al., 2014; Urízar, 2023).

A substantial body of evidence has revealed a strong link between childhood trauma and a variety of addictive behaviors, extending beyond gambling. Research has repeatedly demonstrated a link between trauma exposure and an increased risk of alcohol misuse, drug dependence, and poorer treatment outcomes in the substance use field (e.g., Khoury et al., 2010; Simpson & Miller, 2002). More recently, studies on behavioral addictions such as gaming disorder have reported that individuals with higher levels of childhood maltreatment also exhibit more severe gaming problems (e.g., Schimmenti et al., 2017; Shi et al., 2020). These findings collectively support a general trauma model of addictive behaviors, suggesting that early adverse experiences contribute to vulnerability across substance-related and behavioral addictions.

## Study rationale

To date, no research—in France or elsewhere—has examined how specific trauma subtypes (e.g., sexual abuse, physical neglect, and emotional neglect) or PTSD/C-PTSD symptom clusters (e.g., hyperarousal versus numbing) predict the severity of online sports betting. Instead, most large-scale studies aggregate trauma into a single score or binary variable (any abuse vs. none), which obscures subtype-specific effects (Moore & Grubbs, 2021; Estevez et al., 2023). However, initial evidence suggests that this level of detail is important. For example, problem gamblers report higher rates of witnessing domestic

violence or physical assault, which are considered interpersonal traumas, than other types of adversity, such as parental divorce (Roberts et al., 2017). Additionally, interpersonal abuse is generally considered to confer a greater risk of addiction than one-time events (Dvorak et al., 2013). From a clinical perspective, childhood trauma and PTSD symptoms exert independent influences on substance-use trajectories (Mergler et al., 2018). This implies that the type of trauma and the quality of post-traumatic symptomatology (e.g., intrusive flashbacks versus C-PTSD's dysregulation) likely have differential relationships with gambling frequency, expenditure, and coping motives. Addressing this gap by combining CTQ subscales with ITQ symptom clusters will clarify trauma-specific risk pathways and inform targeted, trauma-informed interventions for online sports bettors.

## Method

### Participants

A total of 135 online bettors (78 men, 57 women; M = 37.5, SD = 10.7) were recruited through online platforms and a research panel. Inclusion criteria required participants to be 18 years or older, proficient in French, and score above 5 on the Canadian Problem Gambling Index (CPGI; Ferris & Wynne, 2001). The dataset is available at the following online repository: https://osf.io/n64j2/

### Measures

**Canadian Problem Gambling Index (CPGI).** The CPGI is a 9-item scale classifying gamblers into four categories: non-problem, low-risk, moderate-risk, and problem gamblers. Responses are rated on a Likert scale from 0 (never) to 3 (almost always), with scores ≥8 indicating problem gambling (Ferris & Wynne, 2001). We used the standard French translation of the 9-item PGSI embedded in the Canadian Problem Gambling Inventory. The original instrument has strong reliability and validity indices, and the French version is the reference tool used in French epidemiology and clinical practice (OFDT, s.d.). In our sample, internal consistency was excellent (α = 0.90; ω = 0.91).

**Socio-Demographic and Gambling Habits Questionnaire.** A 25-item questionnaire collected data on participants' gender, age, education, occupation, family status, gambling frequency, spending, substance use, and past help-seeking behavior.

**The Mental Health Inventory-5 (MHI-5).** The Mental Health Inventory-5 (MHI-5; Rumpf et al., 2001) assesses psychological distress and well-being using five items rated on a 1 (always) to 6 (never) Likert scale, converted to a 0–100 scale where lower scores indicate poorer mental health. We used the French mental health 5-item index (from Leplège et al., 1998). The French SF-36 is well validated, with good reliability/validity. In our sample, α = 0.80; ω = 0.81.

**Gambling Motives Questionnaire-Financial (GMQ-F).** The GMQ-F assesses motivations for gambling, focusing on three primary motives: enhancement, coping, and social motivation. The GMQ-F consists of 15 items rated on a 4-point Likert scale ranging from 1 ("almost never/ never") to 4 ("almost always"). Higher scores on each subscale indicate greater motivation for that particular gambling reason (Stewart & Zack, 2008). We used the validated French GMQ-F (Devos et al., 2017), which demonstrates the expected four-factor structure and good internal reliability. In our sample, α = 0.89; ω = 0.89.

**Childhood Trauma Questionnaire-Short Form (CTQ-SF).** The Childhood Trauma Questionnaire-Short Form (CTQ-SF; Bernstein et al., 2003) is a 28-item self-report measure evaluating childhood abuse and neglect across five domains: emotional abuse, physical abuse, sexual abuse, emotional neglect, and physical neglect. We used the validated French CTQ-SF (Paquette et al., 2004). French studies report good psychometric properties and, more recently, confirmatory models supporting robust structure in large Francophone samples. In our sample, the global CTQ score showed α = 0.93.
**International Trauma Questionnaire (ITQ).** The International Trauma Questionnaire (ITQ; Cloitre et al., 2018) is an 18-item scale assessing PTSD and complex PTSD symptoms based on ICD-11 criteria. Responses range from 0 (not at all) to 4 (extremely), with higher scores indicating greater PTSD severity. We used the validated French ITQ (Cyr et al., 2022), which shows the expected factor structure and good internal consistency, convergent/divergent validity, and test-retest reliability in French-speaking samples. We scored the ITQ at subscale level, distinguishing between ITQ-PTSD symptoms (items 1–6) and ITQ-DSO symptoms (items 10–15). For the analyses, we used the 12-item ITQ symptom mean (range 0–4), which was computed across the PTSD and DSO symptom items, excluding the functional impairment items. Screening outcomes are reported as probable PTSD/CPTSD according to the ITQ diagnostic algorithm.

## Procedure

Study participants were directed to the study via an online link disseminated through multiple channels. Upon accessing the link, participants were presented with an information sheet that delineated the study's purpose, procedures, and ethical considerations. They were required to provide informed consent before proceeding to the questionnaires. The online survey was designed to take approximately 20 to 30 min to complete, and all responses were de-identified to ensure the confidentiality of the participants.

## Statistical analysis

All statistical analyses were performed using Jamovi (Version 2.6.22). Descriptive statistics (see Table 1 and 2), including means, standard deviations, and frequencies, were computed for key variables such as PTSD symptoms, childhood trauma, and gambling severity. To test H1, multiple linear regression was conducted to assess whether PTSD symptoms (ITQ scores) and childhood trauma (CTQ-SF scores) predicted gambling severity (CPGI categories; see Table 3). To test H2, multiple regression examined the interaction effects of PTSD symptoms, sociodemographic factors (age, gender), and gambling motives (GMQ-F scores) on gambling severity (see Table 4). Special attention was given to the moderating roles of gender and social motivation.

**Ethics statement:** All procedures involving human participants performed in this study were in accordance with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

## Results

### Descriptive statistics

Table 1 presents descriptive characteristics for the sample. Among participants with complete ITQ data (n = 124), the mean total ITQ score was 42.43 (SD = 15.50). Cluster-level endorsement rates were 52.4 % for re-experiencing, 50.8 % for avoidance, 61.3 % for sense of threat, 68.6 % for affective dysregulation, 53.2 % for negative self-concept, 54.0 % for disturbances in relationships, and 50.8 % for both PTSD- and DSO-related functional impairment. Applying the ICD-11 ITQ algorithm, probable PTSD was indicated in 36/124 (29.03 %) and probable CPTSD in 27/124 (21.77 %), with CPTSD superseding PTSD.

**Hypothesis 1.** Multiple regression analysis showed that PTSD symptoms and childhood trauma significantly predicted gambling severity (R² = 0.398, F(12, 109) = 6.01, *p* < .001). Significant predictors included CTQ-Sexual Abuse (β = −0.416, *p* < .001), indicating a negative association with gambling severity, and CTQ-Physical Neglect (β = 0.273, *p* = .036), suggesting a positive link. Poorer mental health (MIH5) also increased gambling severity (β = −0.287, *p* = .004). Other trauma and demographic factors were non-significant.

<table><caption>**Table 1**
Sample characteristics and ITQ screening outcomes.</caption><thead><tr><th>Measure</th><th>N</th><th>Mean (SD) or n (%)</th><th>Median [Min, Max]</th></tr></thead><tbody><tr><td><strong>Sociodemographics</strong></td><td></td><td></td><td></td></tr><tr><td>Age (years)</td><td>132</td><td>38.36 (10.79)</td><td>37 [18, 69]</td></tr><tr><td>Sex, men</td><td>135</td><td>78 (57.78 %)</td><td>—</td></tr><tr><td>Sex, women</td><td>135</td><td>57 (42.22 %)</td><td>—</td></tr><tr><td><strong>Gambling status</strong></td><td></td><td></td><td></td></tr><tr><td>Amateur</td><td>108 (80.00 %)</td><td>—</td><td>—</td></tr><tr><td>Semi-pro</td><td>14 (10.37 %)</td><td>—</td><td>—</td></tr><tr><td>Pro</td><td>13 (9.63 %)</td><td>—</td><td>—</td></tr><tr><td><strong>Problem gambling (ICJE/PGSI category)</strong></td><td>135</td><td>135 (100.00 %)</td><td>—</td></tr><tr><td><strong>Motives & mental health</strong></td><td></td><td></td><td></td></tr><tr><td>GMQ-F (mean item)</td><td>124</td><td>2.45 (0.58)</td><td>2.47 [1.00, 3.73]</td></tr><tr><td>MHI-5 (mean item)</td><td>135</td><td>3.46 (0.96)</td><td>3.40 [1.00, 6.00]</td></tr><tr><td><strong>Childhood trauma (CTQ)</strong></td><td></td><td></td><td></td></tr><tr><td>CTQ “young” (mean item)</td><td>129</td><td>1.70 (0.89)</td><td>1.23 [1.00, 5.00]</td></tr><tr><td>Emotional abuse (threshold met)</td><td>134</td><td>59 (44.03 %)</td><td>—</td></tr><tr><td>Sexual abuse (threshold met)</td><td>134</td><td>132 (98.51 %)</td><td>—</td></tr><tr><td>Physical neglect (threshold met)</td><td>134</td><td>119 (88.81 %)</td><td>—</td></tr><tr><td>Physical abuse (threshold met)</td><td>134</td><td>53 (39.55 %)</td><td>—</td></tr><tr><td>Denial (threshold met)</td><td>134</td><td>0 (0.00 %)</td><td>—</td></tr><tr><td><strong>ITQ (ICD-11)</strong></td><td></td><td></td><td></td></tr><tr><td>ITQ total (0–72)</td><td>124</td><td>42.43 (15.50)</td><td>42 [18, 79]</td></tr><tr><td>PTSD clusters endorsed (0/1)</td><td>124</td><td>RE 52.4 %; AV 50.8 %; TH 61.3 %</td><td>each: median 1 [0, 1]</td></tr><tr><td>DSO clusters endorsed (0/1)</td><td>124</td><td>AD 68.6 %; NSC 53.2 %; DR 54.0 %</td><td>each: median 1 [0, 1]</td></tr><tr><td>Functional impairment (0/1)</td><td>124</td><td>PTSD 50.8 %; DSO 50.8 %</td><td>each: median 1 [0, 1]</td></tr><tr><td><strong>Screened caseness (ITQ algorithm)<sup>†</sup></strong></td><td>124</td><td>PTSD: 36 (29.03 %); CPTSD: 27 (21.77 %)</td><td>—</td></tr></tbody></table>

Notes. Values reflect complete data per variable; ITQ complete cases *n* = 124. CPGI category is “Problematic” for all participants by inclusion criteria. Cluster variables are binary (1 = at least one item endorsed at ≥ “moderately” within the 2-item cluster). Functional impairment variables indicate ≥1 of the three impairment items endorsed. ITQ screening rule: PTSD = endorsement in each PTSD cluster (re-experiencing, avoidance, sense of threat) plus PTSD-related impairment. CPTSD = PTSD criteria plus endorsement in each DSO cluster (affective dysregulation, negative self-concept, disturbances in relationships) plus DSO-related impairment. CPTSD supersedes PTSD when both are met.

**Hypothesis 2.** PTSD symptom severity based on the ITQ 12-item symptom mean was a marginally significant predictor of gambling severity (β = 0.21, *p* = .067). Gambling motives (GMQ-F) showed a positive but nonsignificant association (β = 0.18, *p* = .070). Interactions involving ITQ with GMQ-F, age, and sex did not reach significance (all *p* > .05); the Age × ITQ term approached but did not meet the conventional threshold (β = −0.17, *p* = .070). Among covariates, poorer mental health (MHI-5) predicted greater gambling severity (β = −0.34, *p* < .001), CTQ-Sexual Abuse was negatively associated with severity (β = −0.41, *p* = .001), and CTQ-Physical Neglect showed a positive trend (β = 0.24, *p* = .056).
<table><caption>**Table 2**

Correlation matrix between study variables (Pearson's r).</caption><thead><tr><th>#</th><th>Variable</th><th>1</th><th>2</th><th>3</th><th>4</th><th>5</th><th>6</th><th>7</th><th>8</th><th>9</th><th>10</th><th>11</th></tr></thead><tbody><tr><td>1</td><td>CTQ-Emotional Abuse</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td>2</td><td>CTQ-Physical Abuse</td><td>.79***</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td>3</td><td>CTQ-Sexual Abuse</td><td>-.70***</td><td>-.69***</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td>4</td><td>CTQ-Physical Negligence</td><td>-.41***</td><td>-.33***</td><td>.50***</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td>5</td><td>CTQ-Denial</td><td>-.14</td><td>.11</td><td>.17</td><td>.68***</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td>6</td><td>ICJE (PGSI)</td><td>.28**</td><td>.22*</td><td>-.31***</td><td>.00</td><td>-.02</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td>7</td><td>MHI-5</td><td>-.16</td><td>-.12</td><td>.19*</td><td>.21*</td><td>.21*</td><td>-.48***</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td>8</td><td>CTQ (total)</td><td>.87***</td><td>.83***</td><td>-.87***</td><td>-.69***</td><td>-.33***</td><td>.25**</td><td>-.22*</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td>9</td><td>CTQ-Young</td><td>.68***</td><td>.75***</td><td>-.64***</td><td>-.25**</td><td>.04</td><td>.23**</td><td>-.13</td><td>.71***</td><td>—</td><td>—</td><td>—</td></tr><tr><td>11</td><td>GMQ-F</td><td>.28**</td><td>.24**</td><td>-.12</td><td>-.01</td><td>.02</td><td>.38***</td><td>-.18*</td><td>.19*</td><td>.32***</td><td>-.30***</td><td>—</td></tr></tbody></table>

Note: Due to missing data, pairwise Ns vary by variable (approx. 122–135). Two-tailed tests: *p* < .05*, *p* < .01**, *p* < .001***. ICJE = Indice canadien du jeu excessif (PGSI); MHI-5 = Mental Health Inventory-5; CTQ = Childhood Trauma Questionnaire.

<table><caption>**Table 3**

Regression analysis for Hypothesis 1 (Outcome: Gambling severity).</caption><thead><tr><th>Predictor</th><th>B</th><th>SE B</th><th>95 % CI [LL, UL]</th><th>β</th><th>t (108)</th><th>p</th></tr></thead><tbody><tr><td>Intercept</td><td>18.82</td><td>0.39</td><td>[18.04, 19.60]</td><td>0.02</td><td>47.99</td><td>&lt; 0.001</td></tr><tr><td>CTQ-Emotional Abuse</td><td>0.25</td><td>0.80</td><td>[-1.33, 1.83]</td><td>0.04</td><td>0.31</td><td>.754</td></tr><tr><td>CTQ-Physical Abuse</td><td>-0.42</td><td>0.84</td><td>[-2.08, 1.24]</td><td>-0.08</td><td>-0.50</td><td>.616</td></tr><tr><td>CTQ-Sexual Abuse</td><td>-3.18</td><td>0.81</td><td>[-4.79, -1.58]</td><td>-0.48</td><td>-3.93</td><td>&lt; 0.001</td></tr><tr><td>CTQ-Physical Negligence</td><td>1.62</td><td>0.68</td><td>[0.28, 2.97]</td><td>0.31</td><td>2.40</td><td>.018</td></tr><tr><td>CTQ-Denial</td><td>-0.47</td><td>0.82</td><td>[-2.09, 1.15]</td><td>-0.07</td><td>-0.58</td><td>.565</td></tr><tr><td>CTQ-Young (mean)</td><td>-0.98</td><td>0.74</td><td>[-2.44, 0.48]</td><td>-0.16</td><td>-1.33</td><td>.187</td></tr><tr><td>MHI-5 (mean)</td><td>-1.76</td><td>0.56</td><td>[-2.86, -0.65]</td><td>-0.30</td><td>-3.16</td><td>.002</td></tr><tr><td>GMQ-F (mean)</td><td>1.76</td><td>0.92</td><td>[-0.06, 3.58]</td><td>0.18</td><td>1.92</td><td>.058</td></tr><tr><td>Sex (women vs men)</td><td>1.20</td><td>0.81</td><td>[-0.42, 2.81]</td><td>0.22</td><td>1.47</td><td>.145</td></tr><tr><td>Age</td><td>-0.06</td><td>0.04</td><td>[-0.13, 0.02]</td><td>-0.11</td><td>-1.39</td><td>.168</td></tr><tr><td>ITQ (mean)</td><td>0.79</td><td>0.69</td><td>[-0.58, 2.16]</td><td>0.12</td><td>1.14</td><td>.256</td></tr></tbody></table>

Note. B = unstandardized coefficient; β = standardized coefficient. CI = confidence interval. Outcome variable labelled “gambling severity” (ICJE/PGSI continu). Sex: 0 = men, 1 = women (label “women vs men”). Values rounded according to APA norms; exact *p* value reported (three digits) or < 0.001.

## Discussion

This study examined the relationships between childhood trauma, PTSD, impulsivity, gambling motivations, and the severity of problematic online gambling. Findings indicate that childhood trauma, especially sexual abuse and physical neglect, along with poor mental health, was significantly associated with gambling severity. PTSD also emerged as a key predictor, reinforcing the link between trauma and gambling behaviors. Unexpectedly, emotional abuse, physical abuse, and cognitive gambling beliefs were not significant predictors, and no significant interaction effects were observed for socio-demographic factors and gambling motivations.

### Childhood trauma and gambling severity

Consistent with previous studies, interpersonal traumas, especially physical abuse and neglect, emerged as strong predictors of betting severity. Physical abuse in childhood was positively associated with greater gambling involvement, consistent with evidence showing that exposure to violence early in life disrupts emotion regulation and fosters

impulsivity (Cyders & Smith, 2008; Stewart & Zack, 2008). Emotional and physical neglect was also associated with higher betting severity, consistent with research showing that unmet childhood needs can lead to low self-esteem and insecure attachments, prompting individuals to seek comfort through gambling (Shin, McDonald & Conley, 2018; Grubbs, Stauner, Exline, Pargament & Lindberg, 2015). Contrary to expectations and much of the literature on sexual trauma and addictions (Spataro et al., 2004), childhood sexual abuse was inversely related to gambling severity. This may reflect avoidance mechanisms or resilience among survivors who steer clear of high-risk activities or a “survivor bias” whereby the most affected individuals disengage from gambling communities (Browne, Hing, Russell, Thomas & Jenkinson, 2019).

These findings highlight the necessity of trauma-informed gambling treatment. Traditional interventions focus on behavioral regulation but may be ineffective for individuals whose gambling stems from unresolved trauma (Yau & Potenza, 2015). Integrating trauma-focused therapies, such as Cognitive Processing Therapy (CPT) or Eye Movement Desensitization and Reprocessing (EMDR), could improve treatment outcomes (Levin et al., 2018). The co-occurrence of PTSD and gambling disorder suggests that comprehensive mental health approaches are needed to address these interrelated conditions (Kessler et al., 2008).

### Mental health, impulsivity, and unexpected findings

Poor overall mental health, as measured by PTSD symptoms and impulsivity, was associated with greater betting severity. This finding supports the idea that people often gamble to alleviate distress (Jiménez-Murcia et al., 2021; Hodgins, Stea & Grant, 2011). However, trait impulsivity alone did was not associated with betting severity. This suggests that impulsivity's impact may depend on trauma or psycho-pathology contexts (Cyders & Smith, 2008). Similarly, anticipated sociodemographic interactions (e.g., gender differences) were not significant, perhaps reflecting the de-emphasis of social elements in anonymous online betting (Davis & Avery, 2004).

As said before, contrary to expectations, impulsivity was not associated with predict gambling severity. While previous research links impulsivity to gambling addiction, this study suggests that it may interact with other factors, such as trauma and mental health, in complex ways (Cyders & Smith, 2008). Future research should explore these interactions further. Similarly, anticipated interactions between socio-demographic factors, PTSD symptoms, and gambling motivations were not significant. While gender differences in gambling behaviors have been reported, they may be less relevant in online gambling, where social elements are less pronounced (Davis & Avery, 2004). Larger, more diverse samples are needed to clarify these relationships.

### Limitations and future research

This study has several limitations. Its cross-sectional design
<table><caption>**Table 4**
Multiple regression predicting gambling severity.</caption><thead><tr><th>Predictor (variable)</th><th>B</th><th>SE B</th><th>95% CI [LL, UL]</th><th>β</th><th>t(98)</th><th>p</th></tr></thead><tbody><tr><td>Intercept</td><td>-0.46</td><td>0.42</td><td>[-1.30, 0.38]</td><td>—</td><td>-1.08</td><td>.281</td></tr><tr><td>CTQ-Emotional Abuse (CTQ-Emotional_Abuse)</td><td>0.55</td><td>0.79</td><td>[-1.02, 2.11]</td><td>0.10</td><td>0.69</td><td>.490</td></tr><tr><td>CTQ-Physical Abuse (CTQ-Physical_Abuse)</td><td>-0.95</td><td>0.80</td><td>[-2.54, 0.65]</td><td>-0.18</td><td>-1.18</td><td>.241</td></tr><tr><td>CTQ-Denial (CTQ - Denial)</td><td>0.33</td><td>0.80</td><td>[-1.25, 1.91]</td><td>0.05</td><td>0.41</td><td>.680</td></tr><tr><td>MIH-5 (mean) (MIH5_M)</td><td>-2.02</td><td>0.56</td><td>[-3.12, -0.91]</td><td>-0.34</td><td>-3.62</td><td>&lt; 0.001</td></tr><tr><td>CTQ-Young (mean) (CTQ_Young_M)</td><td>-0.93</td><td>0.70</td><td>[-2.32, 0.46]</td><td>-0.16</td><td>-1.32</td><td>.188</td></tr><tr><td>GMQ-F (mean) (GMQ-F_M)</td><td>1.70</td><td>0.93</td><td>[-0.14, 3.54]</td><td>0.18</td><td>1.83</td><td>.070</td></tr><tr><td>Age (Age)</td><td>-0.02</td><td>0.04</td><td>[-0.11, 0.06]</td><td>-0.05</td><td>-0.56</td><td>.574</td></tr><tr><td>Sex (women vs men) (Sex1)</td><td>0.77</td><td>0.85</td><td>[-0.91, 2.46]</td><td>0.14</td><td>0.91</td><td>.364</td></tr><tr><td><strong>ITQ symptom mean (ITQ)</strong></td><td><strong>1.32</strong></td><td><strong>0.72</strong></td><td><strong>[-0.10, 2.74]</strong></td><td><strong>0.21</strong></td><td><strong>1.85</strong></td><td><strong>.067</strong></td></tr><tr><td>CTQ-Sexual Abuse (CTQ-Sexual_Abuse)</td><td>-2.70</td><td>0.82</td><td>[-4.34, -1.07]</td><td>-0.41</td><td>-3.28</td><td>.001</td></tr><tr><td>CTQ-Physical Neglect (CTQ - Physical_Negligence)</td><td>1.29</td><td>0.67</td><td>[-0.03, 2.62]</td><td>0.24</td><td>1.94</td><td>.056</td></tr><tr><td>Age × Sex</td><td>0.08</td><td>0.09</td><td>[-0.10, 0.26]</td><td>0.15</td><td>0.85</td><td>.396</td></tr><tr><td>GMQ-F × Sex</td><td>0.45</td><td>1.92</td><td>[-3.36, 4.27]</td><td>0.05</td><td>0.24</td><td>.814</td></tr><tr><td>Sex × ITQ</td><td>0.73</td><td>1.09</td><td>[-1.44, 2.90]</td><td>0.11</td><td>0.67</td><td>.506</td></tr><tr><td><strong>Age × ITQ</strong></td><td><strong>-0.10</strong></td><td><strong>0.06</strong></td><td><strong>[-0.22, 0.01]</strong></td><td><strong>-0.17</strong></td><td><strong>-1.83</strong></td><td><strong>.070</strong></td></tr><tr><td>GMQ-F × ITQ</td><td>1.65</td><td>0.97</td><td>[-0.28, 3.57]</td><td>0.14</td><td>1.69</td><td>.093</td></tr><tr><td>GMQ-F × Age</td><td>-0.00</td><td>0.08</td><td>[-0.17, 0.16]</td><td>-0.00</td><td>-0.05</td><td>.957</td></tr><tr><td>GMQ-F × Age × Sex</td><td>-0.03</td><td>0.16</td><td>[-0.35, 0.30]</td><td>-0.03</td><td>-0.17</td><td>.864</td></tr><tr><td>Age × Sex × ITQ</td><td>0.16</td><td>0.11</td><td>[-0.07, 0.38]</td><td>0.26</td><td>1.40</td><td>.164</td></tr><tr><td>GMQ-F × Sex × ITQ</td><td>2.74</td><td>1.89</td><td>[-1.01, 6.49]</td><td>0.24</td><td>1.45</td><td>.151</td></tr><tr><td>GMQ-F × Age × ITQ</td><td>-0.14</td><td>0.09</td><td>[-0.32, 0.04]</td><td>-0.13</td><td>-1.50</td><td>.138</td></tr><tr><td>GMQ-F × Age × Sex × ITQ</td><td>0.09</td><td>0.18</td><td>[-0.27, 0.46]</td><td>0.09</td><td>0.52</td><td>.606</td></tr></tbody></table>

Note. B = unstandardized coefficient; β = standardized coefficient. CI = confidence interval. Sex coding: 0 = men, 1 = women. SE and p heteroscedasticity-robust.

precludes causal inferences, and self-report measures may introduce response biases. Additionally, the sample, recruited online, may not fully represent the broader population of online bettors. Future research should incorporate longitudinal designs and clinical assessments to strengthen findings.

Despite these limitations, this study underscores the critical role of childhood trauma, PTSD, and mental health in problematic online gambling. Addressing these factors in intervention programs may enhance gambling disorder treatment and prevention efforts. What's more, all study measures were self-report, which introduces well-known constraints, including recall and social desirability biases, transient state influences, and common-method variance. Self-report measures do not establish clinical diagnoses; structured interviews remain the gold standard (e.g. CAPS-5 and the International Trauma Interview for ICD-11 PTSD/CPTSD). Nevertheless, the instruments used here have strong psychometric support: the ITQ shows acceptable internal consistency and factorial validity across cultures, the PCL-5 exhibits high internal consistency, convergent/discriminant validity and good diagnostic utility, and dissociation was assessed with well-established tools (e.g. the DES-II) that demonstrate good reliability. Furthermore, BPD features measured via the BSL/BSL-23 and the MSI-BPD have been shown to demonstrate satisfactory reliability and validity in prior studies. Future research should further investigate the psychological mechanisms underlying these relationships.

### Clinical and preventive implications

The present findings suggest that conventional cognitive-behavioral treatments for gambling, which typically target cognitive distortions and promote alternative leisure activities, should incorporate trauma-informed components. First, cognitive restructuring should link gambling urges to specific post-traumatic triggers so clients can learn to reinterpret wagering impulses as hyperarousal or avoidance responses rooted in earlier adversity (Ledgerwood & Milosevic, 2015). Behavioral experiments conducted in simulated betting settings can incorporate grounding strategies, such as the 5-4-3-2-1 sensory technique, to interrupt dissociative states often accompanying post-traumatic stress (Imperatori et al., 2017).

Second, arousal-regulation skills should be embedded throughout treatment. Brief in-session practices, such as paced breathing or progressive muscle relaxation introduced before examining live odds,

enable clients to regulate trauma-related tension instead of using gambling as a quick form of relief (Cloitre et al., 2021).

Systematic risk stratification can help tailor participant prevention according to trauma status. For example, routine intake assessments using the Childhood Trauma Questionnaire and the International Trauma Questionnaire can identify clients with elevated post-traumatic symptoms. Individuals with high PTSD severity may benefit most from integrating trauma-focused therapies, such as cognitive processing therapy or EMDR, into the relapse-prevention curriculum (Tsurumi et al., 2014). Those who score high on physical neglect should receive modules that bolster self-esteem and provide reward-based activities that compensate for unmet childhood needs (Shin et al., 2018). Conversely, clients with extensive histories of sexual abuse may exhibit treatment avoidance. In these cases, resilience enhancement and flexible engagement strategies could improve retention and mitigate dropout risk (Spataro et al., 2004).

Finally, a stepped-care framework can be considered. For instance, clients at low to moderate risk could receive standard cognitive behavioral therapy (CBT) supplemented by brief, trauma-informed skills training. In contrast, those with complex trauma profiles require multidisciplinary care combining specialized trauma therapy, peer support for survivors, and case management to address co-occurring psychosocial challenges. The ITQ is widely used to estimate population prevalence and to characterise clinical cohorts under ICD-11. In a U. S. survey, past-month prevalence was 3.4% for PTSD and 3.8% for CPTSD; in a nationally representative Irish survey, estimates were 5.0% and 7.7%, respectively. A recent systematic review/meta-analysis synthesised general-population ITQ caseness across regions. In treatment-seeking samples (e.g., veterans), CPTSD often exceeds PTSD and shows distinctive comorbidity/severity profiles. Our use of dimensional ITQ scores aligns with our predictive aims; the added descriptives (Table 1) facilitate benchmarking against this epidemiological and clinical literature

### Conclusion

This study highlights childhood trauma, PTSD, and mental health as key predictors of gambling severity. These findings suggest that trauma-informed care should be integrated into gambling treatment strategies. While some anticipated interactions were not significant, the study contributes valuable insights into the psychological factors underlying
online gambling addiction. Future research should continue exploring these complexities to develop more effective interventions.

## Funding statement

This research did not receive any specific grants from funding agencies in the public, commercial, or not-for-profit sectors.

## Ethics approval statement

All procedures involving human participants performed in this study were in accordance with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

## Data availability statement

The dataset is available at the following online repository: https://osf.io/n64j2/

## Patient consent statement

Informed consent was obtained from all participants included in the study.

## Permission to reproduce material from other sources

Not applicable

## Clinical trial registration

Not applicable

## CRediT authorship contribution statement

**Maeva d'Agostino:** Writing – original draft, Visualization, Methodology, Investigation, Data curation, Conceptualization. **Samantha Tessier:** Supervision, Methodology, Investigation, Conceptualization. **Oulmann Zerhouni:** Writing – review & editing, Formal analysis, Data curation. **Lucia Romo:** Writing – review & editing, Supervision, Resources, Project administration, Methodology, Conceptualization.

## Declaration of competing interest

Maeva d'Agostino, Samantha Tessier, Oulmann Zerhouni, and Lucia Romo declare that they have no conflict of interest.

## Acknowledgements

Not applicable.

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