The increasing use of aggressive cancer treatments has highlighted the importance of behavioral interventions in managing the aversive side effects of these therapies. While various behavioral methods have been proven effective in reducing acute treatment-related pain, these interventions are typically implemented only after a patient has accepted treatment. However, an important question remains: do all patients accept treatment? What drives a patient's attitude toward treatment, and what mechanisms underlie their response?

To address these questions, this research proposes a behavioral framework that analyzes patients' responses to treatment, focusing on the mechanisms that influence their decision to accept or reject treatment. The framework assumes that both patients and healthcare providers have access to certain sets of information. Providers, constrained by a limited set of treatment options, use a Markov Decision Process to optimize treatment methods. Patients, on the other hand, base their decision to accept or reject treatment on their risk perception and imitation behavior. This approach offers a novel perspective on the interplay between patient behavior and treatment optimization, contributing to the development of more effective strategies in cancer care.

Bio:

The speaker is a Research Associate in the Department of Mathematics at the University of Toronto. Previously, Dr. Mortaza Baky Haskuee served as a Research Associate at the Fields Institute for Research in Mathematical Sciences, contributing to the Mathematics for Public Health (MfPH) project from January 2023 to July 2024. Since April 2021, Dr. Baky Haskuee has been a visiting professor at ADERSIM, collaborating with LIAM at York University. During his time at LIAM, he has contributed to various research projects and co-authored papers published in top journals. Dr. Baky Haskuee received his PhD in 2010 and subsequently joined the Department of Financial Engineering at K.N.T. Technical University Tehran as an Assistant Professor. In 2013, he received his first postdoctoral fellowship to contribute to a research project co-funded by the Hungarian government and the European Commission (TÁMOP 4.2.2 A–11/1/KONV-2012-0058), which aimed at developing a complex macro-regional (GMR) impact analysis model for Hungary to study the economic effects of environmental innovations.