Can Labor Pain be Reduced by Open Placebo Intervention? A Bayesian Account for Labor Pain

The human nervous system continuously processes a potentially overwhelming stream of signals from bodily senses, which induces uncertainty. To reduce this uncertainty, the brain transforms sensory input into a reliable perception of the world. According to the Bayesian hypothesis of perception, based on probabilistic estimation, conscious perception is shaped by both the current state of sensory information and by past experiences, associative learning, stored memories, and beliefs. This framework is particularly relevant for explaining the phenomenon of pain, including individual differences in pain perception and response.

The focus of the present work is pain during childbirth, representing a major acute pain event. Pain during childbirth is a complex and unique experience with both sensory and emotional components, embedded within a defined physiological process. A key concept of the Bayesian model related to pain perception is the placebo phenomenon, which offers a compelling explanation for the analgesic placebo response.

The overarching aim of this study is to evaluate whether the Bayesian model can account for changes in pain perception during labor following open placebo administration, as well as the involvement of expectations and personality traits.

The study will be conducted at Hillel-Yaffe Medical Center, with the participation of 120 pregnant women. The research will be divided into two stages. The first stage will occur during the prenatal period, while participants are in a pain-free state. During this stage, questionnaires will be completed to assess expectations and personality traits, and the Focused Analgesia Selection Test (FAST) will be administered to evaluate within-subject variability in pain intensity. The second stage will take place during labor and will involve an open placebo intervention, during which pain levels and analgesic consumption will be monitored.