The willingness to continue using wearable devices among the elderly: SEM and FsQCA analysis

BMC Med Inform Decis Mak. 2023 Oct 16;23(1):218. doi: 10.1186/s12911-023-02336-8.

Abstract

Background: With population aging and the scarcity of resources for elderly individuals, wearable devices pose opportunities and challenges for elderly care institutions. However, few studies have examined the effects of technical characteristics, personal characteristics, and health promotion on the willingness of elderly individuals to continue using wearable devices.

Objective: This study explored the effects of technical characteristics and personal characteristics on the willingness of elderly individuals to continue using wearable devices through health promotion, drawing on the technology acceptance model and the value attitude behaviour model.

Methods: We obtained 265 valid samples through questionnaire surveys and used structural equation modelling (SEM) and fuzzy set qualitative comparative analysis (FsQCA) to clarify the complex causal patterns of elderly people's willingness to continue using wearable devices.

Results: The SEM results showed that perceived usefulness, perceived reliability, self-perceived ageing, and health promotion affected willingness to continue using wearable devices. However, perceived ease of use had no effect. FsQCA showed that elderly individuals are highly willing to continue using wearable devices, yielding five solutions. Perceived ageing was essential in four of these solutions. The impact of perceived ease of use on continued use intention was dynamic and complex.

Conclusions: This study used two methods to provide insight into the willingness of elderly individuals to continue using wearable devices. In addition, this study discussed associated implications, limitations, and future research directions.

Keywords: Elderly; FsQCA; Health promotion; Personal characteristic; Technical characteristic; Wearble devices.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Attitude
  • Humans
  • Intention
  • Latent Class Analysis
  • Reproducibility of Results
  • Wearable Electronic Devices*