Does dispositional mindfulness moderate how individuals engage in their passions? An investigation into video games
Bibliographic record
Abstract
The Dualistic Model of Passion (DMP) is an emerging framework in social psychology that assesses individuals’ passion for an activity. Although a passion parallels the definition for a serious leisure activity, the DMP further differentiates between a harmonious (HP) versus an obsessive (OP) passion, which are associated with adaptive versus maladaptive outcomes, respectively. Building on recent research in the area of mindfulness and the growing interest in problem video gaming, the present study explores the effect of dispositional mindfulness on reports of HP and OP. An online sample of adult video game users (N = 1,124; 68.95% male) completed assessments of their passion for video gaming as well as their dispositional mindfulness. Results revealed a negative association between dispositional mindfulness and OP for video gaming, but no association between dispositional mindfulness and HP for video gaming. Further, a moderation effect was found such that high dispositional mindfulness appears to protect against internalizing an OP for video gaming. Finally, results from a latent profile generally supported the role dispositional mindfulness plays in reducing the severity of OP for video gaming. The implications for theory and positive video game engagement are discussed.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".