Exercise as it relates to Disease/Reducing sedentary behavior in aging adults using smartphone technology
This is an analysis of the journal article "Harnessing Different Motivational Frames via Mobile Phones to Promote Daily Physical Activity and Reduce Sedentary Behavior in Aging Adults" by King et al., 2013.
What is the background to this research?Edit
Applications for smartphones aimed at physical activity and other health behaviors are on the rise however, few are based on behavior theories and studies. A major killer of many older Australians is diseases derived from a sedentary lifestyle and lack of physical activity. This journal article looks at improving the health of sedentary adults using mobile applications on evidence-based theories.
Where is the research from?Edit
The research was conducted by a team of behavioral and exercise scientists, computer scientists, and engineers with approval from the Stanford University School of Medicine.
What kind of research was this?Edit
This study was a case report and randomized control trials. A case report is focused on a series of patients with an outcome of interest and no control group is involved. A Randomized control trial is a controlled clinical trial that randomly assigns participants to two or more groups.
What did the research involve?Edit
The study consisted of eighty adults aged 45 years and older who lived a sedentary lifestyle with little or no physical activity and had limited experience with a smartphone. The participants were separated into three different groups which were given one of three apps to use. Each app is based on motivational frames drawn from behavioral science theory and evidence.
Based on the social cognitive theory which a theoretical perspective in which learning by observing others is the focus of study. Allows the participants to set personalized goals, self-monitor and active problem solving around barriers. The interface of this app uses two basic gauges, similar to a speed gauge, to show the user their daily physical activity amount and their daily sitting amount. This also shows the daily goals for both categories.
Allows participants a social comparison, norms and support from the application and comparing to other social participants. Drawn largely from the social influence theory and perspectives. The social app was represented by a live wallpaper display of the individual avatars representing the user. These avatars would display a different posture depending on how active each participant is.
Focuses on the operant conditioning principles of reinforcement scheduling. This application uses an avatar to reflect the physical activity and sedentary levels of the participant, while also reflecting movements and behaviors. The affect app avatar was represented in the form of a bird which reflected how active or sedentary the participant was throughout the day. Participants needed to perform at least 30 minutes of moderate exercise a day to make the bird "happy".
What were the basic results?Edit
The results of the study showed a significant increase in daily physical activity for all participants. There was an improvement in the daily amount that participants spent time sedentary. The analytic and social app showed a larger decrease in sedentary time than the affect app. The results also reported a positive attitude of the participants towards the use of the smartphones.
What are the implications of this research?Edit
The main limitation of this research was the absence of a control group to compare data against. The advantage of this limitation however allowed researchers a clear idea as to the effects that the smartphone technology had on the lives of sedentary adults.
What conclusion can we take from this research?Edit
The research concluded that the use of smartphone technology can have a benefit to the amount of time older adults spent sedentary or being physically active. With the use of different behavioral theories and evidence, researchers were able to achieve their goal of creating an application that promoted physical activity using mobile phone technology.
1. Faghri, P., Omokaro, C., Parker, C., Nichols, E., Gustavesen, S. and Blozie, E. (2008). E-technology and Pedometer Walking Program to Increase Physical Activity at Work. The Journal of Primary Prevention, 29(1), pp. 73–91. 2. Rabin, C. and Bock, B. (2011). Desired Features of Smartphone Applications Promoting Physical Activity. Telemedicine and e-Health, 17(10), pp. 801–803. 3.Allen, J., Stephens, J., Dennison Himmelfarb, C., Stewart, K. and Hauck, S. (2013). Randomized Controlled Pilot Study Testing Use of Smartphone Technology for Obesity Treatment. Journal of Obesity, 2013, pp. 1–7.
- King, A., Hekler, E., Grieco, L., Winter, S., Sheats, J., Buman, M., Banerjee, B., Robinson, T. and Cirimele, J. (2013). Harnessing Different Motivational Frames via Mobile Phones to Promote Daily Physical Activity and Reduce Sedentary Behavior in Aging Adults. PLoS ONE, 8(4), p.e62613.
- Research.library.gsu.edu. (2016). GSU Library Research Guides: Literature Reviews: Types of Clinical Study Designs. [online] Available at: http://research.library.gsu.edu/c.php?g=115595&p=755213 [Accessed 27 Sep. 2016].
- Bandura A (2006) Toward a psychology of human agency. Psychol Sci 1: 164– 180
- Centola D (2011) An experimental study of homophily in the adoption of health behavior. Science 334: 1269–1272.
- Skinner BF (1981) Selection by consequences. Science 213: 501–504.