Abstract: The current invention concerns a method for predicting a placebo response in an individual, comprising collecting data via—querying said individual on personality and health traits; and/or—performing one or more social learning and/or (bio)physical tests on said individual; characterized in that said data is used in a mathematical model stored on a computer for computing a correlation between the input data, thereby attributing a Scoring Factor to said individual, whereby said Scoring Factor is a measure of propensity to raise a placebo response and/or a measure of the intensity of said response.

Abstract: A method is described for predicting a pain response in a subject suffering from cancer-induced bone pain (CIBP). Data is collected from the subject by querying the subject on personality and/or health traits, and/or performing one or more social learning and/or (bio)physical tests by or on the subject. The data is used in a set of mathematical models to attribute one or more Scoring Factors to the subject. The Scoring Factor is a measure of the propensity of the subject to raise a response to a pain stimulus or a treatment strategy; and/or a measure of the intensity of the response of the subject.

Abstract: A method for predicting a placebo response in an individual, suffering from or at risk of developing a pain disorder is described. Data is collected from the individual by querying the individual on personality and/or health traits, or performing one or more social learning and/or (bio)physical tests on said individual. The data is used in a mathematical model which attributes a Scoring Factor to the individual. The Scoring Factor is a measure of propensity to raise a placebo response and/or a measure of the intensity of the response for the pain disorder. Tools for implementing the method and preferred uses of the method are described.