Can Playing Massive Multiplayer Online Role Playing Games (MMORPGs) Help Older Adults?
Bibliographic record
Abstract
Gerontology researchers have demonstrated that social interaction has profound impacts on the psychological wellbeing of older adults. This paper addresses the question of whether and how playing Massive Multiplayer Online Role-Playing Games (MMORPGs) help older adults. We analyzed the relationships of older adults’ social interactions in Massive Multiplayer Online Role-Playing Games (MMORPGs) to three social-psychological factors (i.e., loneliness, depression and social support). A total of 176 web surveys were usable from the 222 respondents aged 55 years or more who played World of Warcraft and were recruited online to complete the survey. It was found that enjoyment of relationships and quality of guild play had strong impacts on older adults’ social and emotional wellbeing. Specifically, higher enjoyment of relationships was related to higher social support as well as lower levels of loneliness. Higher quality of guild play was related to higher levels of social support and lower levels of loneliness and depression.
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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 | 0.006 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".