Technology readiness of patients and its association with intention to use nursing robots: latent profile analysis.

BACKGROUND: Robotic technology is transforming healthcare by delivering more precision, convenience, and efficiency, as seen in applications like blood collection robots. However, the full potential of such innovations hinges critically on patient acceptance. To systematically understand the drivers of intention to use, the concept of technological readiness-an individual's stable propensity to embrace new technologies-provides a valuable lens. Nevertheless, the demographic profile of technological readiness and its specific relationship with the intention to use nursing robots remain underexplored. OBJECTIVE: This study aimed to identify profiles of technology readiness among patients, analyze the factors influencing these profiles, and investigate the relationship between different profiles and the intention to use blood collection robots. METHODS: In this study, data on technology readiness and intention to use were collected from 331 patients between December 2024 and February 2025 through a cross-sectional survey. Latent profile analysis (LPA) was employed to assess population heterogeneity in patients' technology readiness, whereas logistic regression analysis was applied to identify factors associated with the intention to use blood collection robots. RESULTS: Potential profiling revealed three distinct technology readiness populations: conservative avoiders (47.7%), ambivalent adopters (18.5%), and active adopters (33.8%). The results of the three-profile classification are related to the intention to use blood collection robots. The results clearly show that the intention to use the blood collection robot by patients belonging to conservative avoiders (profile 1) was weaker and statistically significant than both active adopters (profile 3) and ambivalent adopters (profile 2). While profile 2 has a high intention to use, it also has a high level of insecurity and discomfort. Interestingly, the group of patients with low education levels is more likely to be attributed to active adopters. The results of the multiple regression analysis on patients' intention to use revealed significant differences in education level, experience with robots, and potential profiles. CONCLUSIONS: This study reveals the complex psychological characteristics of patient groups when encountering new technologies and their potential relationship with intention to use nursing robots. This suggests that clinical practice should account for patient heterogeneity from standardized procedures to a patient-centered approach. Targeted measures should be proposed to enhance the efficiency of technology implementation and improve patient experience.