Intention to Use Digital Health Among COPD Patients in Europe: A Cluster Analysis

TL;DR

This study identifies two groups of COPD patients in Europe with different intentions to use digital health tools, highlighting factors that influence their adoption.

Contribution

The paper introduces a cluster analysis of COPD patients' intention to use digital health interventions based on psychosocial and digital skill profiles.

Findings

Two clusters emerged: a 'balanced hesitant' group and an 'enthusiastic' group with distinct adoption intentions.

Performance expectancy was a consistent predictor of digital health adoption across both clusters.

Country-specific factors and digital literacy influenced adoption intentions differently among the clusters.

Abstract

Background: Chronic obstructive pulmonary disease (COPD) increasingly strains European health systems amid population ageing. Digital health interventions (DHIs) can reduce hospitalizations and support self-management, yet older patients hesitate to adopt them. Tailored interventions require understanding patient profiles. This study aimed to identify clusters by intention to use DHIs. Methods: Between July 2024 and February 2025, 232 COPD patients (mean age 65; 61% female) across seven European countries completed surveys covering sociodemographic and Unified Theory of Technology Acceptance (UTAUT) constructs. Intention to use DHIs was categorized as positive, neutral, or negative. Weighted UTAUT scores were clustered using Gower distance and Partitioning Around Medoids. Associations were visualized with multiple correspondence analysis and heat maps; differences were tested with the chi-square test. Results: Intention to adopt DHIs varied across countries, with the highest in the Netherlands. Two clusters emerged. Cluster 1, the ‘balanced hesitant’ group (n = 104), showed mixed intentions (38% positive, 40% neutral, 21% negative). Barriers included low performance expectancy and limited digital skills (both p < 0.05). Cluster 2, the ‘enthusiastic’ group (n = 128), demonstrated strong adoption intentions, with 84% positive intention. Enablers included low effort expectancy and complex disease (p < 0.01). Across both clusters, performance expectancy predicted intention. Conclusions: Digital health adoption among COPD patients is shaped by psychosocial and digital skill profiles. Hesitant users benefit from expectation-based information about DHIs, digital literacy training and peer support. Enthusiasts require ease of integration. Performance expectancy is a consistent driver of adoption, whereas country-specific factors should guide strategies.

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