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Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment
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Smartphone Use Predicts Being an "Active Couch Potato" in Sufficiently Active Adults
Curtis Fennell1,2,3, Andrew Lepp1,2,3, Jacob Barkley1,2,3
1Exercise and Nutrition Science, University of Montevallo, Montevallo, Alabama (CF).
American Journal of Lifestyle Medicine
|December 17, 2021
Summary
High smartphone use, not TV, is linked to the "active couch potato" phenomenon in adults who meet physical activity guidelines. This sedentary behavior involves extensive screen time despite regular exercise.
Area of Science:
- Public Health
- Behavioral Science
- Physical Activity Research
Background:
- Sedentary behavior is a growing public health concern.
- The
- active couch potato
- describes individuals meeting physical activity guidelines but engaging in high sedentary behavior.
- The role of digital media, particularly smartphones, in this behavior is not fully understood.
Purpose of the Study:
- To examine the association between smartphone use, television viewing, and the active couch potato phenomenon.
- To differentiate the impact of screen-based sedentary behaviors in physically active adults.
Main Methods:
- Survey data collected from 328 sufficiently active adults (aged 18-80).
- Assessment of daily smartphone use, television viewing, physical activity, and total sedentary behavior.
- Definition of active couch potato: meeting physical activity guidelines and ≥8 hours/day sedentary behavior.
Main Results:
- 39% of participants were classified as active couch potatoes.
- Active couch potato status was significantly associated with higher daily smartphone use (4.95 ± 4.5 hours).
- Television viewing was not significantly associated with active couch potato status.
Conclusions:
- Smartphone use is a significant predictor of the active couch potato phenomenon in sufficiently active adults.
- Television viewing does not appear to contribute to this specific sedentary behavior pattern.
- Interventions targeting sedentary behavior should consider the impact of smartphone usage patterns.
