Abstract
Background: Obesity has become a severe health problem in the world. Even a moderate 5% weight loss can significantly reduce the prevalence of metabolic syndrome, which can be vital for preventing comorbidities caused by the obesity. Health Behavior Change Support Systems (hBCSS) emphasize an autogenous approach, where an individual uses the system to influence one’s own attitude or behavior to achieve his or her own goal. Regardless of promising results, such health interventions technology has often been considered merely as a tool for delivering content that has no effect or value of its own. More research on actual system features is required.
Objectives: The objective of this study is to describe how users perceive persuasive software features designed and implemented into a support system.
Methods: The research medium in this study is a web-based information system designed as a lifestyle intervention for participants who are at risk of developing a metabolic syndrome or who are already suffering from it. The system was designed closely following the principles of the Persuasive Systems Design (PSD) model and the Behavior Change Support Systems (BCSS) framework. A total of 43 system users were interviewed for this study during and after a 52 week intervention period. In addition, the system’s login data and subjects’ Body Mass Index (BMI) measures were used to interpret the results.
Results: This study explains in detail how the users perceived using the system and its persuasive features. Self-monitoring, reminders, and tunneling were perceived as especially beneficial persuasive features. The need for social support appeared to grow along the duration of the intervention. Unobtrusiveness was found to be very important in all stages of the intervention rather than only at the beginning.
Conclusions: Persuasive software features have power to affect individuals’ health behaviors. Through their systematicity the PSD model and the BCSS framework provide effective support for the design and development of technological health interventions. Designers of such systems may choose, for instance, to implement more self-monitoring tools to help individuals to adjust their personal goals with the system’s offerings better
