Feasibility of Popular m-Health Technologies for Activity Tracking Among Individuals with Serious XXXX .

@entity1 @entity162 @entity1032 @entity308 @entity353 @entity28 @entity10688 @entity161
UNASSIGNED: Abstract Obesity prevalence is nearly double among individuals with @entity1032 ( @entity1032 ), including @entity161 spectrum disorders, @entity162 , or major @entity308 , compared with the general population. Emerging mobile health (m-health) technologies are increasingly available and offer the potential to support lifestyle interventions targeting @entity353 , yet the practical feasibility of using these technologies in this high-risk group has not been established. We evaluated the feasibility and acceptability of popular m-health technologies for activity tracking among overweight and @entity28 individuals with @entity1032 . We provided wearable activity monitoring devices (FitBit [San Francisco, CA] @entity10688    or Nike Inc. [Beaverton, OR] FuelBand) and smartphones (Apple [Cupertino, CA] iPhone(  ) 4S) for accessing the smartphone application for each device to @entity1 with @entity1032 enrolled in a @entity353 program. Feasibility of these devices was measured by the frequency of use over time. Acceptability was measured through qualitative follow-up interviews with @entity1 . Ten @entity1 with @entity1032 wore the devices for a mean of 89% (standard deviation=13%) of the days in the study. Five @entity1 wore the devices 100% of the time. @entity1 reported high satisfaction, stating the devices were easy to use, helpful for setting goals, motivational, and useful for self-monitoring. Several @entity1 liked the social connectivity feature of the devices where they could see each other's progress on the smartphone application, noting that "friendly" competition increased motivation to be more physically active. This study supports using popular m-health technologies for activity tracking among individuals with @entity1032 . These findings can inform the design of @entity353 interventions targeting this vulnerable @entity1 population.
