Graduation Year


Document Type




Degree Name

Doctor of Philosophy (Ph.D.)

Degree Granting Department

Information Systems and Decision Sciences

Major Professor

Kaushik D. Dutta, Ph.D.

Committee Member

Theresa Beckie, Ph.D.


Health Information Technology, Center Based Cardiac Rehabilitation, Design Science Research, Behavior Change Interventions, Chronic Disease Management


This dissertation presents research that employs design science research (DSR) methodology to develop and evaluate a high-fidelity prototype of a home-based cardiac rehabilitation (HBCR) system to support self-management of chronic cardiovascular diseases like coronary heart disease (CHD) and to offer secondary prevention against other chronic diseases with similar risk factors. While the population of coronary heart disease (CHD) patients requiring cardiac rehabilitation (CR) continues to expand, lack of access and other barriers to center based cardiac rehabilitation (CBCR) presents a huge challenge. A mobile phone and wearable device based technological system can offer an HBCR program for CHD. By following DSR guidelines we have designed a digital health intervention system for use in an HBCR program. The system we propose combines ‘human-expert’ intelligence with machine intelligence to enhance the decision-making capability of a health coach. We initially evaluated the prototype of our system with ten patients with CHD over 13 weeks through a single arm, quasi-experimental study (Sengupta et al. 2020a). The evaluation reveals a significant positive impact of the preprogrammed intervention messages on participants’ step count and walking duration on the same and the next day. Since increased step count and walking duration positively correlates with the improved heart health, we can directly infer that our proposed system is beneficial as a tool for secondary prevention of CHD (Sengupta et al. 2020b). Mobile health information technology (HIT) interventions (like our HBCR system) offer a new paradigm in chronic disease management by empowering patients with information, tools, and alerts and engaging them in the self-management of their own diseases. However, we know little about how these technologies work and how we can design features to sustain their use over time. We also explore these issues using the affordance actualization concept to examine two types of affordance actualization offered by these technologies: intended and unintended. We hypothesize the independent and joint effects of these affordance actualizations, by integrating affordance with goal setting theory and nudge theory. The proposed hypotheses are empirically tested using a field trial of our home-based cardiac rehabilitation prototype for patient self-management of coronary heart disease. Panel data from this study, analyzed using multi-level, zero-inflated Poisson, and negative binomial models, provide support for our hypotheses. This study explicates the complex interplay between intended and unintended affordance actualization, draws attention to the actualization of affordances in unexpected ways (Sengupta et al. 2020c), which can potentially explain both effective use and misuse of technologies, elaborates how we can build process oriented models of technology-related behaviors by drawing on conscious and subconscious cognitive processes linked to technological affordance actualization, and demonstrates how HIT design can benefit from considering unintended affordance actualization as a behavioral intervention for chronic care patients.