Counselling conversation summarization
In today’s fast-moving life, people are so much busy that they barely get time to focus on their mental health. With increasing stress and hypertension, everyone has a risk of developing a mental health disorder. With the increasing number of people reporting mental health illnesses, the awareness of mental health has also increased in recent times. Efforts are being made to seek aid for mental health issues by taking therapy sessions or by talking to a psychologist. Therapists use many ways to determine the cause and symptoms of illness in a person. One of many ways is “talk therapy”. Through talk therapy, patients talk to a mental health expert and therapists are able to identify the complex symptoms and causes of mental health. They understand the behavior, emotions, and ideas that contribute to the illness. It is a complex process to determine the actual cause of illness in the first session itself. And it is even more complicated to make a record of all the conversations between the patient and the therapist. The therapist writes down notes during the therapy session to make a record for reference in future therapy sessions with the patient. But cannot be relying only on those notes. LCS2 (IIIT Delhi) is currently one of the labs working in the area of digital health under the mental health space.
Need for Summarization after Counselling Unlike general clinical discussions, psychotherapy's core symptoms are hard to distinguish, thus becoming a complex problem to summarize later. A structured counseling conversation may contain discussions about symptoms, history of mental health issues, or the discovery of the patient's behavior. That’s why it is important and necessary to use online counseling conversation summarization that will directly help the therapist. General Summarization Model: Various speech recognition and dialogue summarization has been built with time to help people generate documents and reduce time. In the healthcare sector, various online medical conversation summarization platforms had also been made to provide solutions with patients’ medical data but due to lack of knowledge of such an online platform, it is hardly used by doctors and medical staff. And it is extremely important in mental healthcare to keep a record of the patients’ data and keep critical information like medical history. ConSum Model : Counselling Conversation Summarization in Mental Healthcare ConSum, an online Counselling Conversation Summarization Model, a psychotherapy intervention technique is a multifaceted conversation between a therapist and a patient.
Aseem Srivastava and Yash Kumar Atri, Ph.D. Students – IIIT Delhi, under the guidance of Dr. Tanmoy Chakraborty have been working on this project and developed this model which helps therapists directly in the counseling sessions. Here are some details related to the proposed ConSum model discussed above. ConSum undergoes three independent modules: 1. To assess the presence of depressive symptoms, it filters utterances utilizing the Patient Health Questionnaire (PHQ-9). 2. Classification of essential counseling components that play a major role in summary generation. 3. Propose a problem-specific Mental Health Information Capture (MHIC) evaluation metric for counseling summaries. The main focus of the Consum Model is to summarize the symptoms/reasons, routines, and patient discovery. It Summarizes the whole conversation in meaningful and relevant information with good grammar and linguistics. It makes sure that the summary is completely unbiased. It’s remarkable to see the use of artificial intelligence and deep learning in the current state-of-the-art models. Researchers from LCS2 Lab, IIIT Delhi have used advanced deep learning methods including transformer-based models to build quality counseling summaries. The comparative study shows that ConSum Model improves performance and generates cohesive, semantic, and coherent summaries. It comprehensively analyzes the generated summaries to investigate the capturing of psychotherapy elements (aka counseling components). Human and clinical evaluations of the summary show that ConSum generates quality summaries. Mental health experts from Mpathic.ai validate the clinical acceptability of the ConSum summarization model. The ConSum application has been approved to be commercialized for therapists and other mental health experts worldwide. The first version of the application will be rolled out soon.