Evaluation of Technology Acceptance and Electronic Health (Ehealth) Literacy of Patients Undergoing Radiotherapy

Examining the acceptance, trust and communication of a novel patient interaction system in a user-centered manner is essential due to several critical factors highlighted in the literature. The integration of technology into healthcare significantly changes the roles and interactions between healthcare stakeholders, including patients, healthcare providers and the technology itself (Kim et al., 2024). As the use of artificial intelligence (AI) and other advanced technologies in clinical decision-making increases, it is crucial to understand how patients perceive and interact with these systems. Research by Kim et al. (2024) emphasizes that patients have different preferences regarding AI autonomy, so it is important to involve them in defining and regularly reassessing the scope of AI support to ensure it is both effective and acceptable (Kim et al., 2024).

Trust in technology is a key factor influencing its acceptance and effectiveness. Patient trust in AI and other digital health tools can be influenced by their experience, perceived reliability and transparency of the technology. Li (2024) discusses that trust is strengthened when the benefits and reliability of the technology are clearly demonstrated. For example, studies on digital twins in antenatal care show that the perceived reliability of AI predictions and personalized care plays an important role in building trust (Li, 2024). Addressing trustworthiness concerns through user-centered design can help build trust by ensuring that the technology is transparent, explainable, and aligned with patients' needs and values.

Effective communication between patients and healthcare providers is an essential prerequisite for shared decision-making, a core principle of patient-centered care. Hao et al. (2024) state that patient-centered shared decision-making improves healthcare outcomes and patient satisfaction by ensuring that patients are well informed and actively involved in their care decisions (Hao et al., 2024). The integration of technology must promote this communication and not hinder it. For example, patient-centered decision aids can improve the quality of decisions and patient satisfaction if they are designed to support shared decision making by providing clear, personalized information that patients can discuss with their healthcare providers (Hao et al., 2024).

Patient acceptance of the technology is also crucial for its successful introduction. Acceptance is influenced by factors such as ease of use, perceived benefits and the extent to which the technology fits into patients' existing routines and workflows. Research by Kambhamettu et al. (2024) suggests that explainability and meaningful engagement with the technology are key to promoting adoption. This aligns with the findings that by involving patients in the development process, potential barriers to acceptance can be identified and removed (Kambhamettu et al., 2024). By ensuring that the technology is intuitive and meets patients' needs, user-centered design practices can facilitate the seamless integration of technology into patients' healthcare.

In addition, Corti (2024) emphasizes the importance of continuous assessment and adjustment of patient-technology interactions to ensure alignment with patient expectations and preferences. This approach ensures that the technology remains relevant and effective over time (Corti, 2024).

The basis for any integration of digital solutions into patient care, for example the integration of ePROMs into patient care, is a high level of digital health literacy. As part of this study, the digital health literacy of patients undergoing radiotherapy will now be examined in a qualitative and quantitative study . In addition, factors influencing digital health literacy and technology acceptance that could prevent these patients from being integrated into digital health solutions will be identified.

Inclusion criteria

• Indication for carrying out radiotherapy
• Capacity to consent
• At least 18 years of age
• Sufficient knowledge of the German language

Exclusion criteria

• Lack of capacity to consent
• Age <18 years