Valuable Genomes: Taxonomy and Archetypes of Business Models in Direct-to-Consumer Genetic Testing

Abstract

Background Recent progress in genome data collection and analysis technologies has led to a surge of direct-to-consumer (DTC) genetic testing services. Owing to the clinical value and sensitivity of genomic data, as well as uncertainty and hearsay surrounding business practices of DTC genetic testing service providers, DTC genetic testing has faced significant criticism by researchers and practitioners. Research in this area has centered on ethical and legal implications of providing genetic tests directly to consumers, but we still lack a more profound understanding of how businesses in the DTC genetic testing markets work and provide value to different stakeholders. Objective The aim of this study was to address the lack of knowledge concerning business models of DTC genetic testing services by systematically identifying the salient properties of various DTC genetic testing service business models as well as discerning dominant business models in the market. Methods We employed a 3-phased research approach. In phase 1, we set up a database of 277 DTC genetic testing services. In phase 2, we drew on these data as well as conceptual models of DTC genetic testing services and iteratively developed a taxonomy of DTC genetic testing service business models. In phase 3, we used a 2-stage clustering method to cluster the 277 services that we identified during phase 1 and derived 6 dominant archetypes of DTC genetic testing service business models. Results The contributions of this research are 2-fold. First, we provided a first of its kind, systematically developed taxonomy of DTC genetic testing service business models consisting of 15 dimensions in 4 categories. Each dimension comprises 2 to 5 characteristics and captures relevant aspects of DTC genetic testing service business models. Second, we derived 6 archetypes of DTC genetic testing service business models named as follows: (1) low-cost DTC genomics for enthusiasts, (2) high-privacy DTC genomics for enthusiasts, (3) specific information tests, (4) simple health tests, (5) basic low-value DTC genomics, and (6) comprehensive tests and low data processing. Conclusions Our analysis paints a much more complex business landscape in the DTC genetic testing market than previously anticipated. This calls for further research on business models and their effects that underlie DTC genetic testing services and invites specific regulatory interventions to protect consumers and level the playing field.

Archetypes of Gamification: Analysis of mHealth Apps

“…To answer our research question, we employed a 3-step research approach that was informed by the studies of Remane et al [ 28 ] and Thiebes et al [ 29 ] and is shown in Figure 1 . As a first step, we set up a database of pertinent gamified mHealth apps from the Apple App Store and Google Play Store.…”

“…In this work, we draw on the taxonomy proposed by Schmidt-Kraepelin et al [ 20 ] as our classification scheme, because it (1) provides the opportunity of classifying holistic gamification approaches as it is not limited to single game elements, (2) has been explicitly built for health care apps, and (3) provides a concrete set of dimensions with mutually exclusive and collectively exhaustive characteristics. Further, the taxonomy has been derived based on the guidelines proposed by Nickerson et al [ 35 ], which combine inductive and deductive reasoning and have been extensively used to develop taxonomies for phenomena in health care [ 29 ]. Past research has shown that taxonomies developed based on the guidelines by Nickerson et al [ 35 ] are suitable classification schemes with regard to the development of archetypes through cluster analysis [ 28 , 29 ].…”

“…Further, the taxonomy has been derived based on the guidelines proposed by Nickerson et al [ 35 ], which combine inductive and deductive reasoning and have been extensively used to develop taxonomies for phenomena in health care [ 29 ]. Past research has shown that taxonomies developed based on the guidelines by Nickerson et al [ 35 ] are suitable classification schemes with regard to the development of archetypes through cluster analysis [ 28 , 29 ]. The taxonomy proposed by Schmidt-Kraepelin et al [ 20 ] consists of 12 dimensions, each consisting of 2 to 3 mutually exclusive characteristics, with a total of 30 characteristics.…”

“…The taxonomy enables us to classify gamification approaches employed in pertinent gamified mHealth apps from the Apple App Store and Google Play Store. In addition, we use the 2-step clustering approach of Punj and Stewart [ 27 ], which has been employed in similar research [ 28 , 29 ], for identifying archetypes of gamification approaches in pertinent mHealth apps. In doing so, we are able to unveil established best practices in the design and implementation of gamification for mHealth apps and to analyze to what extent those gamification approaches are influenced by the underlying desired health-related outcomes.…”

Editorial

“…The deep and continuously increasing integration of digital technologies into our everyday lives, e. g. by mobile solutions, will revolutionize our view on health care. Quantifying one's health status will increasingly not solely be applicable within health care institutions but also to other organizations such as, for example, direct-to-consumer genetic testing providers [3]. It will rather become an ongoing task helping to predict, maintain or improve the quality of life, both for individuals and society.…”