JMIR Publications

ABSTRACT

The recent onset of the COVID-19 pandemic and the social distancing requirement has created a further demand for virtual groups. Advances in artificial intelligence (AI) may offer novel solutions to the management challenges such as the lack of emotional connections within virtual groups’ interventions. Using typed text from Online Support Groups (OSGs), AI can help identify the potential risk of mental health concerns, alert group facilitator(s), and automatically recommend tailored resources while monitoring patient outcomes. We developed and evaluated an ‘Artificial Intelligence–based Co-facilitator (AICF)’ to monitor OSG participants’ distress through a real-time analysis of texts posted during the support group sessions. Specifically, AICF 1. generated participant profiles with discussion topic summaries and emotion trajectories for each session, 2. identified participant(s) at-risk for increased emotional distress and alerted the therapist for follow-up, and 3. automatically suggested tailored recommendations based on participant needs. The current study reported on the mixed-method evaluation of AICF, including therapists’ opinions, as well as quantitative measures. AICF’s ability to detect distress was evaluated by the patient real-time emoji check-in, the Linguistic Inquiry and Word Count (LIWC), and the Impact of Event Scale. Although quantitative results showed only some validity of AICF’s ability in detecting distress, the qualitative results showed that AICF was able to detect real-time issues that are amenable to treatment, thus allowing therapists to be more proactive in supporting every group member on an individual basis. However, therapists are concerned about the liability of AICF’s distress detection function. Future works will look into wearable sensors and facial cues in the video-conferencing to overcome the inconsistencies.