Theory-Based Problem Formulation and Ideation in mHealth Analysis and Recommendations

2022 ◽  
Vol 34 (4) ◽  
pp. 0-0

This article reports on an investigation into how to improve problem formulation and ideation in Design Science Research (DSR) within the mHealth domain. A Systematic Literature Review of problem formulation in published mHealth DSR papers found that problem formulation is often only weakly performed, with shortcomings in stakeholder analysis, patient-centricity, clinical input, use of kernel theory, and problem analysis. The study proposes using Coloured Cognitive Mapping for DSR (CCM4DSR) as a tool to improve problem formulation in mHealth DSR. A case study using CCM4DSR found that using CCM4DSR provided a more comprehensive problem formulation and analysis, highlighting aspects that, until CCM4DSR was used, weren’t apparent to the research team and which served as a better basis for mHealth feature ideation.

2015 ◽  
pp. 1116-1133 ◽  
Author(s):  
Aline Dresch ◽  
Daniel Pacheco Lacerda ◽  
Paulo Augusto Cauchick Miguel

Author(s):  
Nadhmi Gazem ◽  
Azizah Abdul Rahman ◽  
Faisal Saeed ◽  
Noorminshah A. Iahad

This article contends that design science research (DSR) has emerged as an important approach in information systems (IS) research. The design science research roadmap (DSRR) model describes the process of using the DSR in IS in great detail. Unfortunately, the existing literature does not address the task of demonstrating the use of the DSRR in detail by conducting a real case study. This article aims to examine the implementation of the DSRR with real IS research activities. The construction of a systematic innovation framework to solve problems for small and medium enterprises (SMEs) is used as a case study for demonstration purposes. This article shows that the DSRR provides very useful guidance, since it covers almost all the necessary steps to conduct DSR in the information systems field. The illustrations provided with each step of the DSRR in this article will help other researchers, especially novice researchers, to gain a comprehensive understanding of the use of the DSRR model.


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