Evaluation of End-User Participation in Artificial Intelligence Nursing Projects

Area of Science:

• Health Informatics
• Nursing Technology
• Artificial Intelligence in Healthcare

Background:

• Artificial Intelligence (AI) is increasingly relevant in healthcare, especially nursing, but faces significant user acceptance challenges.
• Enhancing end-user participation during AI development and implementation is crucial for improving acceptance rates.
• A validated measurement tool is needed to quantify end-user involvement in AI projects within nursing.

Purpose of the Study:

• To propose and develop a scale for measuring the degree of end-user participation in AI development and implementation for nursing projects.
• To assess end-user participation and empowerment activities within AI initiatives from a project manager's perspective.
• To provide a quantifiable metric for evaluating user involvement to inform future AI adoption strategies in nursing.

Main Methods:

• Development and evaluation of a novel scale using the qualitative-analytical COARSE method.
• The instrument comprises 11 items across two sub-scales: 'activities for active participation of end-users' and 'empowerment activities'.
• The scale is designed to be rated by project managers overseeing AI initiatives in nursing.

Main Results:

• A new 11-item scale was developed to measure end-user participation in nursing AI projects.
• The scale includes sub-scales focusing on active participation and empowerment activities.
• The study emphasizes the importance of understanding the purpose and consequences of measuring end-user participation.

Conclusions:

• The developed scale offers a method for project managers to evaluate end-user participation in nursing AI projects.
• Measuring end-user participation is vital for understanding and potentially improving AI acceptance in healthcare settings.
• Future research should focus on the psychometric validation of the scale, including reliability and validity testing.