Examining Motivations to Play Pokémon GO and Their Influence on Perceived Outcomes and Physical Activity
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Pokémon GO is the most played augmented reality game in history. With more than 44 million players at the peak of its popularity, the game has sparked interest on its effects on the young population's health. OBJECTIVE: This pilot study examined motivations to start playing Pokémon GO among a sample of US college students, and how motivations were associated with perceived outcomes of the playing experience and physical activity derived while playing. METHODS: In November 2016, we asked a sample of 47 US college students (all Pokémon GO players) to complete online surveys and install an ecological momentary assessment (EMA) tool and step counter on their smartphones. The EMA tool prompted a set of questions on playing behavior and physical activity, 3 times per day (12:00 PM, 7:00 PM, and 10:00 PM), for 7 days. We used a factorial analysis to identify 3 distinctive groups of players based on their motivations to start playing Pokémon GO. We tested differences across motivation groups related to 5 unique outcomes using 1-way analysis of variance. RESULTS: We extracted 3 interpretable factors from the clustering of motivations to start playing Pokémon GO: Pokémon and video game fans (n=26, 55% of the sample), physical activity seekers (n=8, 17%), and curious & social (n=13, 28%). The clusters differed significantly on the enjoyment of different aspects of the game, particularly battling, discovering new places, and meeting new people, as well as differences in agreement that playing improved mood and made them more social. Days when playing Pokémon GO were associated with higher number of steps reported at the end of the day, especially among physical activity seekers, but also for Pokémon and video game fans. All groups perceived traffic as a major threat to playing. CONCLUSIONS: Days during which Pokémon GO was played were positively associated with a set of beneficial health behaviors, including higher physical activity levels, more socialization, and better mood. Results, however, depended on personal motivations and expectations when joining the game. These results highlight the importance of taking motivation into account when attempting to extract conclusions from the Pokémon GO phenomenon to enhance future exergames' designs or health interventions.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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