A wearable chatbot-based model for monitoring colorectal cancer patients in the active phase of treatment

Abstract

Colorectal cancer is one of the leading causes of death in the world. This study presents the findings of a prospective non-randomized clinical study for evaluating a new computational model for monitoring colorectal cancer patients in the active treatment phase using artificial intelligence and the Internet of Things. For eight weeks, patients self-reported perceived symptoms and adverse effects, practiced physical activity, and data about their diet. The outcome assessment was based on comparing the intervention and control groups. Patients evaluated the model using the User Experience Questionnaire (UEQ) and the System Usability Scale (SUS). Patients who participated in the model reported signs and symptoms more accurately (control: 64.7%; intervention: 92.3%; p = 0.1038). In the intervention group, physical activity was more effective, and most patients (61.5%) interacted with the chatbot for at least 62.5% of the period. Results indicate that the model contributes to more assertive data collection and greater patient engagement in self-management of symptoms and adverse effects of treatment and cancer. Moreover, the model contributed to increasing the practice of light physical activity by patients. UEQ and SUS scores indicate that the model met users’ expectations and has acceptable usability.