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How to Evaluate Health Applications with Conversational User Interface?
1Bern University of Applied Sciences, Bern, Switzerland.
Studies in Health Technology and Informatics
|June 24, 2020
Summary
This study presents a new evaluation framework for healthcare chatbots, also known as conversational user interfaces (CUIs). This framework helps developers and researchers assess chatbot quality before patient use.
Area of Science:
- Health Informatics
- Human-Computer Interaction
- Artificial Intelligence in Healthcare
Background:
- Conversational user interfaces (CUIs), or chatbots, are increasingly used in healthcare applications, driven by AI advancements and mobile health trends.
- The growing adoption of healthcare chatbots necessitates reliable methods for evaluating their effectiveness and quality.
- Existing evaluations often lack a comprehensive approach, highlighting the need for a structured framework.
Purpose of the Study:
- To introduce a novel evaluation framework specifically designed for healthcare systems utilizing conversational user interfaces (CUIs).
- To provide a structured approach for assessing the quality of health chatbots, aiding developers and researchers.
- To ensure reliable evaluation of chatbot performance and patient interaction before deployment.
Main Methods:
- A systematic review of existing health chatbot applications and relevant literature was conducted to identify key evaluation aspects.
- Evaluation aspects were aggregated and categorized into thematic dimensions.
- The framework was developed by synthesizing these aspects into six core quality categories.
Main Results:
- The developed framework encompasses six key quality dimensions for healthcare chatbots: user experience, linguistic quality, task-oriented functionality, artificial intelligence capabilities, healthcare quality, and system quality.
- These dimensions provide a comprehensive set of attributes for assessing chatbot performance.
- The framework offers a structured approach to selecting relevant quality attributes for evaluation.
Conclusions:
- The proposed evaluation framework offers a systematic method for assessing the quality of healthcare chatbots.
- It supports developers and researchers in ensuring that chatbots meet necessary quality standards before patient use.
- Implementing this framework can lead to more reliable and effective conversational user interfaces in healthcare.
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