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Modeling, a key technique in therapy, uses observational learning to help clients acquire and practice new skills by watching therapists demonstrate desired behaviors. This approach, rooted in Albert Bandura's concept of vicarious learning, plays a significant role in therapeutic interventions for various psychological conditions, including social anxiety, ADHD, and depression.
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Patient-Provider Communication Training Models for Interactive Speech Devices.

Patricia Ngantcha1, Muhammad Amith2, Cui Tao2

  • 1Texas Southern University, Houston, TX, USA.

Digital Human Modeling and Applications in Health, Safety, Ergonomics and Risk Management : Human Body, Motion and Behavior : 12Th International Conference, DHM 2021, Held As Part of the 23Rd HCI International Conference, HCII 2021, Vir
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Summary
This summary is machine-generated.

This study introduces an ontology-based model for training medical students in patient-provider communication using conversational agents. The developed dialogue engine successfully managed 62% of communication links in initial testing.

Keywords:
Conversational agentDental educationDialogue managementOntologyPatient-provider communicationTraining

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Area of Science:

  • Medical Education
  • Artificial Intelligence in Healthcare
  • Human-Computer Interaction

Background:

  • Effective patient-provider communication is crucial for improving patient health outcomes and fostering trust.
  • Training healthcare professionals in communication skills is essential for medical encounters.
  • Speech-enabled conversational agents offer a potential tool for communication skills training.

Purpose of the Study:

  • To design an ontology-based interaction model for training dental and medical students in patient-provider communication.
  • To develop and test a prototype software engine utilizing this model.

Main Methods:

  • Transformed sample communication scripts into a formalized ontology training model.
  • Linked user and machine utterances representing patient-provider communication.
  • Created two instance-based models to test the operational execution with a prototype dialogue engine.

Main Results:

  • The developed dialogue engine demonstrated the capability to handle approximately 62% of the dialogue links within the tested model.
  • The ontology-based interaction model provided a structured approach to simulating patient-provider communication scenarios.

Conclusions:

  • The proposed ontology-based interaction model shows promise as a training tool for enhancing patient-provider communication skills in medical education.
  • Further development is needed to capture more nuanced features of patient-provider communication for eventual pilot deployment.