| Literature DB >> 29958272 |
Apichai Wattanapisit1,2, Udomsak Saengow1,2, Chirk Jenn Ng3, Sanhapan Thanamee4, Nonthakorn Kaewruang1.
Abstract
Pokémon GO becomes the most rapidly downloaded mobile application in history. This study aimed to determine the physical activity of medical students, who played Pokémon GO, and the change in their use of Pokémon GO and physical activity over time. An observational study was conducted. Physical activity was measured by using self-administered questionnaires at baseline (phase 0), 1 month (phase 1) and 3 months (phase 2) post-Pokémon GO download. The changes in physical activity (phase 0 to 1 and phase 1 to 2) were analysed using Wilcoxon Signed Ranked test. The trend (3-point analysis) of physical activity from phase 0, 1 to 2 were analysed using Friedman's test. The relationship between physical activity and time spent gaming was analysed by using Spearman's rank correlation. Twenty-six participants (mean age 22.04±1.70 years) participated in the study. There was no statistically significant change in physical activity during the three-month period (p = 0.45). Only 11 participants (42.3%) were still playing Pokémon GO 3 months after download. The key reasons for playing game were 'have fun' and 'pass time/boredom'. The most common commuting mode to play the game was walking; some drove a car or motorcycle while playing the game. There was no correlation between physical activity and time spent gaming. This study highlights how the lack of sustainability of the game and the motivation behind using Pokémon GO as a game rather than a physical activity app may have undermined the potential of using the game to improve physical activity. Further studies need to explore the reasons for the lack of sustainability and how to combine fun with behavioural change.Entities:
Mesh:
Year: 2018 PMID: 29958272 PMCID: PMC6025865 DOI: 10.1371/journal.pone.0199813
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Demographic characteristics of Pokémon GO players.
| Demographic characteristics | Phase 1 (n = 26) | Phase 2 (n = 11) |
|---|---|---|
| Age (year) mean (SD) | 22.04 (1.70) | 22.20 (1.55) |
| Sex | ||
| • Male | 19 (73.1) | 8 (72.7) |
| • Female | 7 (26.9) | 3 (27.3) |
| Weight status | ||
| • Underweight | 5 (19.2) | 2 (18.2) |
| • Healthy weight | 14 (53.8) | 5 (45.4) |
| • Overweight | 5 (19.2) | 2 (18.2) |
| • Obese | 2 (7.7) | 2 (18.2) |
| Allowance (Baht/month) | ||
| • <5000 | 1 (3.8) | (9.1) |
| • 5000–14999 | 24 (92.3) | 10 (90.9) |
| • ≥15000 | 1 (3.8) | 0 |
| Place of living | ||
| • On campus | 25 (96.2) | 10 (90.9) |
| Underlying illness | ||
| • Yes | 1 (3.8) | 0 |
Data presented as mean (SD) or n (%).
a 35.04 Baht = US$1.
b Bone cyst
Fig 1Comparisons of energy expenditure among participants in phase 0, 1 and 2.
Fig 2Comparisons of sedentary time among participants in phase 0, 1 and 2.
Patterns of and reasons for playing Pokémon GO.
| Playing Pokémon GO | Phase 1 (n = 26) | Phase 2 (n = 11) |
|---|---|---|
| Frequency, n (%) | ||
| • 1–2 days/week | 2 (7.7) | 7 (63.6) |
| • 3–5 days/week | 13 (50.0) | 4 (36.4) |
| • 6–7 days/week | 11 (42.3) | 0 |
| Time spent gaming (minute/week), median (IQR) | 360 (120–630) | 60 (60–80) |
| Reason, n (%) | ||
| • Have fun | 22 (84.6) | 6 (54.5) |
| • Pass time/boredom | 21 (80.8) | 9 (81.8) |
| • Relax/de-stress | 20 (76.9) | 9 (81.8) |
| • Social interaction | 12 (46.2) | 1 (9.1) |
| • Be challenged | 10 (38.5) | 3 (27.3) |
| • Feel excitement | 8 (30.8) | 1 (9.1) |
| • Exercise | 7 (26.9) | 2 (18.2) |
| • Do the impossible | 2 (7.7) | 0 |
| • Learn | 2 (7.7) | 0 |
| Commuting mode, n (%) | ||
| • Walking | 23 (88.5) | 8 (100) |
| • Riding a car | 18 (61.5) | 5 (45.4) |
| • Riding a motorcycle | 13 (50.0) | 5 (45.4) |
| • Running | 6 (23.1) | 1 (18.2) |
| • Cycling | 3 (11.5) | 1 (9.1) |
IQR, interquartile range
Fig 3Relationships between energy expenditure and time spent gaming.
Fig 4Relationships between sedentary time and time spent gaming.