Relationship Between Passion and Motivation for Gaming in Players of Massively Multiplayer Online Role-Playing Games
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Passion represents one of the factors involved in online video gaming. However, it remains unclear how passion affects the way gamers are involved in massively multiplayer online role-playing games (MMORPGs). The objective of the present study was to analyze the relationships between passions and motivations for online game playing. A total of 410 MMORPG players completed an online questionnaire including motives for gaming and the Passion Scale. Results indicated that passionate gamers were interested in relating with others through the game and exhibited a high degree of interest in discovery of the game, gaining leadership and prestige but little interest in escape from reality. However, some differences were observed with respect to the role of the two types of passion in the different types of motivation. Specifically, harmonious passion (HP) predicted higher levels of exploration, socialization, and achievement, in that order, while obsessive passion (OP) predicted higher levels of dissociation, achievement, and socialization. The present findings suggest that HP and OP predict different ways of engaging in MMORPGs and confirm that passion is a useful construct to help understand different motivational patterns demonstrated by MMORPG players.
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.
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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 it