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Development and Evaluation of ClientBot: Patient-Like Conversational Agent to Train Basic Counseling Skills

Development and Evaluation of ClientBot: Patient-Like Conversational Agent to Train Basic Counseling Skills

We used models from the methods described in the study by Tanana et al [24]. These MISC identification models could identify open and closed questions and reflections on a test set with similar performance to human-human reliability (see [24] for full table of results). To track the success of training, the number of open question and reflection codes are tabulated and divided by the total number of utterances, yielding percentages of each type of statement.

Michael J Tanana, Christina S Soma, Vivek Srikumar, David C Atkins, Zac E Imel

J Med Internet Res 2019;21(7):e12529