Journal of Behavioral Addictions最新文献

Background: Gambling content on streaming platforms has gained popularity. Given their intense, cue-laden nature, watching gambling streams may trigger cravings among viewers. At the same time, people who gamble may be motivated to watch gambling streams in an attempt to regulate their cravings.

Methods: We tested these ideas across two preregistered online studies, recruiting i) people who gamble to compare a subgroup of gambling stream viewers with non-viewers (Study 1; nviewers = 221, nnon-viewers = 642), and ii) a group of gambling stream viewers (Study 2; nviewers = 271).

Results: Gambling stream viewers were younger, tended to identify as men, and displayed higher levels of problem gambling and gambling cravings compared to non-viewers. Problem gambling severity was correlated positively with both the motivation to use gambling streams to regulate cravings and with cravings elicited by watching gambling streams.

Discussion: Our findings indicate that while viewers with higher levels of problem gambling may use gambling streams to regulate their cravings, doing so might evoke cravings.

Background: In the Compensatory-Dissociative Online Gaming (C-DOG; Giardina et al., 2024) model, we proposed a continuum from compensatory to dissociative gaming involvement. This continuum represents different degrees of integration between physical and virtual environments with three core processes - Active Escapism, Escape, and Dissociation - and two peripheral processes - Gaming-Related Relaxation and Body-Mind Detachment. Here, we developed and tested a multidimensional measure based on this model.

Method: We capitalized on existing items for measuring escapism and dissociation and we generated new items consistent with the hypothesized model dimensions. A total of 54 items were administered to 1,176 online gamers playing different game genres, together with measures of problematic gaming, passion for gaming, and other psychological distress indicators.

Results: Exploratory and confirmatory factor analyses yielded a six-factor, 36-item structure, with multiple hierarchical regression analyses highlighting unique associations with other psychological constructs assessed.

Discussion: The following factors were identified: (1) Emotional Displacement - redirection of negative emotion into the game with associated relaxation; (2) Absorption - detachment of the player from time and space while gaming; (3) Active Escapism - simulative use of the game to compensate for lack of self-confidence in reaching physical life objectives; (4) Virtual Withdrawal - maladaptive gaming to balance impaired social functioning, predicted by traumatic experiences and pervasive depression; (5) Dissociative Regulation - dysfunctional level of engagement associated with excessive anxiety; (6) Failure Escape - problematic avoidance via gaming related to fear of future failures.

Conclusions: The C-DOG factors identify critical psychological processes associated with problematic gaming, with relevant research and clinical implications.

In their study, Stavropoulos et al. (2023) capitalized on supervised machine learning and a longitudinal design and reported that the User-Avatar Bond could be accurately employed to detect Gaming Disorder (GD) risk in a community sample of gamers. The authors suggested that the User-Avatar Bond is a "digital phenotype" that could be used as a diagnostic indicator for GD risk. In this commentary, our objectives are twofold: (1) to underscore the conceptual challenges of employing User-Avatar Bond for conceptualizing and diagnosing GD risk, and (2) to expound upon what we perceive as a misguided application of supervised machine learning techniques by the authors from a methodological standpoint.

In response to our study, the commentary by Infanti et al. (2024) raised critical points regarding (i) the conceptualization and utility of the user-avatar bond in addressing gaming disorder (GD) risk, and (ii) the optimization of supervised machine learning techniques applied to assess GD risk. To advance the scientific dialogue and progress in these areas, the present paper aims to: (i) enhance the clarity and understanding of the concepts of the avatar, the user-avatar bond, and the digital phenotype concerning gaming disorder (GD) within the broader field of behavioral addictions, and (ii) comparatively assess how the user-avatar bond (UAB) may predict GD risk, by both removing data augmentation before the data split and by implementing alternative data imbalance treatment approaches in programming.

Background: Attention deficit hyperactivity disorder (ADHD) and behavioral addictions (BAs) are highly comorbid but little is known about the effect of anti-ADHD medications on behavioral addiction symptoms. Thus, the aim of this naturalistic prospective study was to investigate the long-term changes on BAs symptoms among methylphenidate-treated adults with a primary diagnosis of ADHD.

Methods: 37 consecutive adult ADHD outpatients completed a baseline and follow-up assessment of ADHD, mood and BAs symptoms (internet, shopping, food, sex addictions and gambling disorder) after one year of methylphenidate (flexible dose) treatment.

Results: Internet addiction test scores pre-treatment were significantly higher than post-treatment scores (p < 0.001). The same trend was seen for the shopping addiction (p = 0.022), food addiction scores (p = 0.039) and sex addiction scores (p = 0.047). Gambling disorder scores did not differ pre and post treatment since none of the included patients reported significant gambling symptoms at baseline. The rate of ADHD patients with at least one comorbid BA was reduced after methylphenidate treatment (51.4% vs 35.1%). The correlation analyses showed a moderate positive correlation between the changes in sluggish cognitive tempo symptoms, cognitive impulsivity, mood and anxiety symptoms and changes in internet addiction symptoms.

Conclusions: This is the first study showing that after one-year of treatment with methylphenidate, adult ADHD patients show a significant reduction on internet, food, shopping and sex addiction symptoms. Further controlled studies with larger samples should replicate these preliminary results and elucidate the role of methylphenidate and other moderator factors (such as concomitant psychological treatments or lifestyle habits changes) on BAs improvements.

Investigating the impacts of addiction policymaking following implementation is important. Effective policies should be considered for emulation elsewhere, whilst ineffective policies should be repealed. Zhou et al. (2024) reported how Mainland Chinese under-18s responded to the 2021 restrictions on their online videogame playtime, which were intended to curb online gaming addiction. However, Zhou et al. failed to mention that Mainland China had previously tried to achieve the same regulatory aim by imposing rules in 2019 that were more lenient than the 2021 rules but nonetheless restricted under-18s' gameplay time. These 2019 restrictions were neither acknowledged as crucial background in the introduction section nor accounted for by Zhou et al. when interpreting their results, thus giving readers the incorrect impression that the 2021 rules were the first ones introduced and that under-18s' gameplay time was not restricted at all prior to 2021. Importantly, Zhou et al.'s entire sample of young people therefore consisted not merely of 'heavy gamers' as they euphemistically described them as, but 'counterplayers' who actively contravened the 2019 rules. The misleading omission of this context is a major limitation and misrepresentation. The results should be interpreted accordingly and not overgeneralised.

Background and aims: Conflicting findings have been reported for the longitudinal course of behavioral addictions, especially for social media addiction (SMA) and work addiction (WA). Therefore, evaluating whether these constructs are more trait-like or state-like might be informative. The aim of the present study was to examine the proportion of variance of SMA and WA symptoms (as defined by the components model of addiction) explained by trait and occasion-specific factors in addition to exploring cross-lagged relationships between SMA and WA.

Methods: Young adults from a representative sample who continuously used social media and worked at least 40 hours a week during the first three waves of the Budapest Longitudinal Study were included (N = 1,551; Females: 50.6%; Age: M = 27.7 years [SD = 4.40]). The Bergen Social Media Addiction Scale and the Bergen Work Addiction Scale were administered in all three waves.

Results: A latent state-trait model with a general trait factor was considered for both SMA and WA. Symptomatic variability in SMA was explained approximately equally by trait and state-like factors, while WA-related symptom variability was mostly attributed to state-like factors. SMA negatively predicted WA over time, while WA showed a positive cross-lagged effect on SMA.

Discussion and conclusions: While the symptoms of WA were more state-like, the trait-like effects were stronger in SMA. Situational influences and previous symptom severities might have to be considered in the screening process.

Background and aims: Mobile phone bans in secondary schools are claimed to reduce student distraction and promote learning and face-to-face socializing. Currently, the evidence on phone bans is limited. The aim of this preregistered study was to evaluate the South Australian mobile phone ban's effects on students' problematic phone use, academic engagement, school belonging, and bullying. The study also sought to identify student variables that predict phone ban compliance.

Methods: As the ban was phased in over 2023, a 2 (phone ban: yes/no) × 2 (time: baseline, 1-month follow-up) repeated-measures design was employed. Students (n = 1,282 at baseline; n = 1,256 at follow-up) in Grades 7 to 12 were recruited from five public secondary schools. Surveys included measures drawn from the Longitudinal Study of Australian Children (LSAC) and the Programme for International Student Assessment (PISA).

Results: Problematic phone use was reported by 2.6% of the sample. Being older and a more frequent user of social media predicted lower phone ban compliance. Linear mixed models indicated that ban and no ban school groups did not differ significantly in terms of problematic phone use, academic engagement, and school belonging. There was slightly higher bullying in the ban group but bullying decreased significantly in both groups.

Discussion: Imposing access restrictions may not affect the underlying psychological mechanisms that drive problematic phone use. Although these results indicate limited to no short-term benefits of the ban, further evaluation with more sensitive methodologies is recommended.

Conclusions: Student-technology interactions in learning institutions should be continually monitored to determine the optimal balance to support student etiquette, learning, and wellbeing.

Background: Compulsive buying-shopping is recognised as a significant mental health concern, yet its aetiology is largely understudied. A known risk factor for compulsive buying-shopping is adverse childhood experiences (ACEs). ACEs are also associated with greater problems regulating emotions, as well as depression and anxiety. These factors are also known to be associated with compulsive buying-shopping problems. In this study, we aimed to test a serial mediation model in which ACEs were associated with compulsive buying-shopping problems via emotion dysregulation, and then emotional psychopathology (depression, anxiety).

Methods: We tested this model cross-sectionally in two large samples (N = 1,868 & 4,742) to evaluate the robustness of the model. Both samples completed self-report measures of ACEs, emotional dysregulation, compulsive buying, depression, and anxiety symptoms.

Results: We found support for indirect effects, and all results were consistent for both samples. ACEs predicted greater emotion dysregulation, which then predicted greater depression and anxiety. In turn, anxiety (but not depression) predicted compulsive buying symptoms.

Discussion and conclusions: Emotion dysregulation and anxiety consistently mediated the relationship between ACEs and compulsive buying symptoms. Both emotion dysregulation and anxiety represent malleable targets in clinical interventions for compulsive buying-shopping problems. Our findings also suggest that anxiety may be a stronger predictor of compulsive buying compared to depression, which may be an important avenue for future researchers to investigate.