Identifying critical success factors for wearable medical devices: a comprehensive exploration


Degerli M., Yildirim S.

UNIVERSAL ACCESS IN THE INFORMATION SOCIETY, 2020 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Volume:
  • Publication Date: 2020
  • Doi Number: 10.1007/s10209-020-00763-2
  • Title of Journal : UNIVERSAL ACCESS IN THE INFORMATION SOCIETY
  • Keywords: Wearable medical device, Acceptance, Critical success factor, Attitude, Healthy living, TECHNOLOGY ACCEPTANCE MODEL, HEALTH-CARE SERVICES, LEAST-SQUARES PLS, OLDER-ADULTS, INFORMATION-TECHNOLOGY, PHYSICAL-ACTIVITY, USER ACCEPTANCE, EHEALTH INTERVENTIONS, ACTIVITY TRACKERS, LATENT-VARIABLES

Abstract

For healthy living, the successful use of wearable medical devices such as smartwatches, smart clothes, smart glasses, sports/activity trackers, and various sensors placed on a body is getting more important as benefits of these devices become apparent. Yet, the existing knowledge about the critical success factors for wearable medical devices needs to evolve and develop further. The main objective of this research is to distill salient constructs to enhance the successful use of wearable medical devices. Specifically, the study aims to identify factors, associated items, and interactions of the relevant factors. A questionnaire has been developed and deployed. The data were collected from 1057 people specifically chosen to represent a wide range of the population. Comprehensive and meaningful inferences have been drawn. Principally, as a fusion of factor analysis and path analysis, a partial least squares structural equation modeling approach consisting of exploratory and confirmatory factor analyses has been applied. In order to assess internal generalization and to precisely identify additional constructs, quasi-statistics have been used. The analyses of data collected revealed 11 salient constructs with 39 items and 18 statistically significant relationships among these constructs. Consequently, composed of distilled constructs and their associations, a novel model with an explanatory power of 73.884% has been approved. Moreover, 13 additional factors were identified as a result of the applied quasi-statistics. This research is the first of its kind on account of its sample characteristics with applied comprehensive methodology and distilled results. This research contributes to the pertinent body of knowledge concerning the critical success factors for wearable medical devices with distilled results. These contributions notably advance the relevant understanding and will be beneficial for researchers and for developers in the field of wearable medical devices.