Lived experience of gaming disorder among people with psychotic disorders: implications for tailored interventions and clinical management
Bibliographic record
Abstract
PURPOSE OF REVIEW: Despite growing recognition of the impact of Gaming Disorder in individuals with psychotic disorders, little is known about the clinical and personal implications of this dual diagnosis. Preliminary data suggest that Gaming Disorder may be associated with increased psychotic symptoms and reduced occupational and social functioning. However, insight from lived experience remain largely absent, despite their importance. RECENT FINDINGS: This review synthesizes recent literature on the comorbidity between Gaming Disorder and psychotic disorders, highlighting the scarcity of research in this emerging field. It also presents preliminary findings from an ongoing qualitative study focussing on the lived experiences of individuals receiving early psychosis intervention. These data focus on participants' motivations for gaming and their perceptions of both positive and negative effects gaming has on their life. SUMMARY: This review underscores the significant lack of data on the dual diagnosis of Gaming Disorder and psychosis. Early qualitative insights reveal diverse gaming motivations, including symptom regulation, anxiety management, cognitive stimulation, and social connection. These first-person accounts emphasize the functional role of gaming and the need for recovery-oriented care. Integrating lived experience into research and clinical practice can improve relevance, support nuanced interventions, and advance our understanding of behavioral addictions in early psychosis.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".