Skip to main content
. 2020 Jun 3;22(6):e17152. doi: 10.2196/17152

Table 2.

Sample characteristics of app-specific community users and nonusers (n=447).

Characteristic Community users (n=193) Nonusers (n=254) P valuea Effect size, Φ Effect size, Cohen d
Age (years), n (%) .005 0.16 N/Ab

18-25 34 (17.7) 77 (30.4)



>25-30 29 (15.1) 46 (18.2)



>30-40 59 (30.6) 65 (25.7)



>40 70 (36.2) 65 (25.7)


Gender identity, n (%) .05 0.09 N/A

Female 159 (82.4) 229 (90.2)



Male 29 (15.0) 24 (9.4)


Ethnicity, n (%) .45 0.11 N/A

White 177 (91.7) 231 (90.9)



Asian 9 (4.7) 9 (3.5)



Indian 2 (1.0) 4 (1.6)



Other 5 (2.6) 10 (4.0)


Structured physical activity (min per week), mean (SD) 357.6 (217.7) 305.4 (196.3) .009 N/A 0.25
Type of app, n (%) .26 0.09 N/A

Tracking 184 (95.3) 234 (92.1)



Guided workouts 5 (2.6) 14 (5.5)



Tracking and workouts 3 (1.6) 2 (0.8)



Other (booking classes or immersive games) 1 (0.5) 4 (1.6)


Physical activity app is used for, n (%) .23 0.11 N/A

All daily activity 18 (9.3) 39 (15.3)



Individual activities 154 (80.0) 184 (72.4)



Group-based activities 0 (0.0) 1 (0.4)



Gym-based activities 10 (5.2) 18 (7.1)



Combination of individual and group-based and gym-based activities 6 (3.1) 6 (2.4)


aStatistical significance is represented by P<.05.

bN/A: not applicable.