Évaluation d’un jeu éducatif en ligne pour améliorer la qualité de vie des aînés
Bibliographic record
Abstract
This article describes and evaluates the educational online game Pour bien vivre, vivons sainement !, which aims to increase players' knowledge about physical aspects of health (nutrition, physical activity, sleep and fatigue), to reduce the risk situations, to highlight the importance of social interactions with family members and friends and to increase emotional well-being. In this exploratory study, the impact of the game on the quality of life was measured for 56 players aged between 50 and 90 who completed pre/post questionnaires. The results show an improvement in their perceivded physical well-being, social welfare and psychological well-being. The game is beneficial to both men and women. Regardless of age, the digital game improves their perception of quality of life. In addition, the older you are, the more one considers the online game strengthens social connections. Finally, the players more experienced in the use of technology, benefit more from online playing.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".