How much does Women, Pain & Mind earn?

WOMEN, PAIN & MIND is an educational game encompassing 21 different diseases and/or types of chronic pain which are typical for women. The game is aimed at health professionals (doctors, physiotherapists, psychologists, nurses) and patients (mainly with one or more of the 21 types of pain). Its dynamics are based on the answers (right or wrong) that the player gives when asked about the most diverse topics related to the experience of pain in each of the 21 divisions. Winning the game, then, de…

WOMEN, PAIN & MIND is an educational game encompassing 21 different diseases and/or types of chronic pain which are typical for women.
The game is aimed at health professionals (doctors, physiotherapists, psychologists, nurses) and patients (mainly with one or more of the 21 types of pain). Its dynamics are based on the answers (right or wrong) that the player gives when asked about the most diverse topics related to the experience of pain in each of the 21 divisions. Winning the game, then, depends on getting the answers right rather than getting them wrong.
At the starting point the player hypothetically suffers from acute pain, transient in nature. From then on, he/she follows a path ending in Chronic Pain - this is the Path of Pain. The coming and going of the player's icon along this path is governed, first, by his successes or errors in qualifying statements about pain as True or False; and second, by the discretion of a roulette triggered after the player is informed of the outcome when answering each question. The points indicated by the roulette determine whether the icon moves up or down on the Path of Pain. It falls in the direction of Chronic Pain and rises in the opposite direction.
Along the Path of Pain, and depending on where the icon lands, there are also unforeseen events or random factors that can delay or speed the player's movement throughout the Path of Pain.
The game allows the player to face a virtual competitor and only ends when he/she definitively wins or loses. The data base is sufficiently robust and its exhaustion is unlikely.