Epic adventures and emotional journeys: How participation in comic conventions and live action role plays is associated with psychosocial outcomes
Bibliographic record
Abstract
Abstract Aim Our aim was to examine the association of visiting comic conventions (including cosplay) and attending live-action role-playing games (LARPs) with psychosocial outcomes (in terms of mental health, subjective well-being, and social disconnectedness). Subject and methods Data were taken from a quota-based sample (representing the general German adult population aged 18 to 74 years, n = 5000). The average age was approximately 47 years. Participation in comic conventions (including cosplay) and LARP events were key independent variables. Psychometrically sound tools were used to quantify the psychosocial outcomes. Adjusted linear regression models were applied. Results Individuals visiting comic conventions had significantly poorer mental health (depressive and anxiety symptoms, social withdrawal) than non-participants. They also had higher loneliness and perceived social isolation levels, but lower objective social isolation levels. They did not differ from non-participants in terms of well-being outcomes. Individuals attending LARPs also had more depressive and anxiety symptoms but did not differ in terms of social withdrawal. They had higher perceived social isolation levels but had lower objective social isolation levels. Furthermore, they had more favorable well-being outcomes than non-participants. Cosplay during comic conventions and current attendance of LARPs were associated with both positive and negative outcomes. Conclusion Visitors to comic conventions and LARPs sometimes had poorer psychosocial outcomes relative to non-visitors, especially in the area of mental health. However, LARP participants had better well-being outcomes than non-participants. This knowledge can help identify specific groups at risk of poor psychosocial outcomes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".