Nurses' perspectives on AI-Enabled wearable health technologies: opportunities and challenges in clinical practice.

BACKGROUND

Wearable health technologies, such as smartwatches, biosensor patches, and fitness trackers, have evolved from basic monitoring tools to advanced medical-grade devices capable of continuous health tracking. The integration of artificial intelligence (AI) enhances their utility by enabling real-time data analysis, early diagnosis, and personalised disease management. Adoption accelerated during the COVID-19 pandemic, reinforcing their role in remote care. However, concerns regarding data privacy, accuracy, cost, and reduced human interaction persist. This study explores nurses' perceptions, awareness, and trust in AI-enabled wearable devices, identifies facilitators and barriers to adoption, and assesses demographic influences on attitudes.

METHODS

A total of 611 nurses were recruited using purposive sampling from educational hospitals in Saudi Arabia. Data were collected through an online structured questionnaire comprising demographic items, Likert-scale statements, and multiple-choice questions. Descriptive statistics and non-parametric tests (Kruskal-Wallis and Mann-Whitney U) were used to examine group differences.

RESULTS

Findings revealed generally positive attitudes toward AI-enabled wearables, with nurses acknowledging their potential to support personalised care, chronic disease management, and healthcare efficiency. However, data accuracy, affordability, and technical reliability emerged as prevalent concerns. Statistically significant differences were observed based on age (p < 0.001), education level (p = 0.001), and workplace setting (p < 0.05), with younger nurses and those in hospital settings expressing greater confidence in AI-driven health insights.

CONCLUSION

While AI-enabled wearable devices are perceived as promising tools in nursing practice, concerns regarding data reliability, cost, and over-reliance on AI must be addressed. Structured training, institutional support, and clear guidelines are essential to ensure successful integration into clinical workflows and optimise their use in patient-centred care.

CLINICAL TRIAL NUMBER

Not applicable.