Analysing the Association Between User Perceptions and Usage Patterns of Digital Personalised Care Platforms Using...

Area of Science:

• Digital Health
• Health Informatics
• Technology Acceptance Models

Background:

• Digital personalized care platforms are increasingly vital in healthcare delivery.
• Understanding user adoption is crucial for the success of health technologies.
• The extended Unified Theory of Acceptance and Use of Technology (UTAUT) provides a framework for evaluating technology adoption.

Purpose of the Study:

• To investigate the relationship between user perceptions and actual usage of the ADLIFE Digital Personalized Care Platform.
• To identify key factors influencing the adoption and engagement with digital health solutions among healthcare professionals and patients.
• To assess the applicability of the extended UTAUT model in the context of a digital personalized care platform.

Main Methods:

• Data collection from healthcare professionals and patients/informal caregivers across multiple pilot sites.
• Utilized the extended Unified Theory of Acceptance and Use of Technology (UTAUT) model to measure user perceptions.
• Analyzed correlations between UTAUT constructs (e.g., usability, performance expectancy, technology anxiety) and platform usage metrics.

Main Results:

• Significant correlations were identified between usability factors and platform usage.
• Performance expectancy and technology anxiety were found to be significant predictors of platform adoption.
• User perceptions strongly influenced actual usage patterns, highlighting the importance of user experience.

Conclusions:

• User-centered design and robust support systems are critical for optimizing digital health platforms.
• Addressing usability and performance expectations can enhance user engagement and adoption of digital health tools.
• Findings provide actionable insights for improving the design and implementation of personalized digital care solutions.