The Mediating Role of Problematic Use of Loot Boxes Between Internet Gaming Disorder and Online Gambling Disorder: Cross-Sectional Analytical Study
Bibliographic record
Abstract
Background: The video game industry has introduced a new form of monetization through microtransactions. A controversial example has been the so-called "loot boxes" (LBs) as virtual objects, which are randomized and bought with legal money. In recent years, LBs have come to connect 2 distinct problem behaviors, namely internet gaming disorder (IGD) and online gambling disorder (OGD). Many association studies have been conducted on the 3 constructs, but few have delved into the relationship of problematic use of LBs (PU-LB) with IGD and OGD. Objective: This study aims to explore the mediating role of the PU-LB between IGD and OGD. Methods: This cross-sectional and analytical study used incidental sampling in 24 Spanish schools. The final sample consisted of 542 participants (male: n=523, 96.5%; age: range 11-30 y) who played video games, bought LBs, and had gambled online in the last 12 months. Participants then completed the Spanish versions of the Internet Gaming Disorder Scale-Short Form, Online Gambling Disorder Questionnaire, and PU-LB scale. Results: IGD scores were found to be significantly associated with both PU-LB (r=0.473, P<.001) and OGD (r=0.209, P<.001). Moreover, PU-LB was significantly associated with OGD (r=0.351, P<.001). The structural equation model results indicated that IGD had no significant direct effect on OGD (P=.903). However, the indirect effect of IGD on OGD through PU-LB was significant (P<.001). Therefore, PU-LB fully mediated the relationship between IGD and OGD. Furthermore, these results were found in the subsamples of both minors (<18 y) and young adults (≥18 y). Conclusions: It is suggested that there is a mediation effect of problematic LB use between internet gambling and online gambling problems in both minors and young adults. This has potential practical implications by providing more evidence on how LBs have become a hinge feature between 2 clinically relevant and independent issues. In this regard, adequate industry self-regulation is needed, and effective legislation for the protection of minors is necessary.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".