A method of classifying media according to user propensities for addictive behavior, the method comprising: obtaining, by a computing device , a physiological state data as a function of a physical sample; identifying, by the computing device, a user propensity for addictive behavior associated with a human subject as a function of the physiological state data and a behavioral model , wherein the user propensity for addictive behavior identifies an addictive behavior from a predetermined plurality of addictive behaviors; receiving, by the computing device, a media item to be transmitted to a device operated by the human subject; extracting, from the media item, a plurality of media item content elements; classifying each content element of the plurality of media item content elements to a media item object of a plurality of media item objects using an object classifier ; grading the media item with a grade level according to a number of appearances and/or proportion of media item objects associated with the user propensity for addictive behaviour of the plurality of media item objects; blocking transmission of the media to the device operated by the human subject if the grade level matches or exceeds a threshold level for exclusion; receiving, from a remote device , an indication that the human subject has engaged in a problematic behavior associated with the user propensity for addictive behavior; and upon receiving the indication from the remote device: lowering the threshold level; and blocking transmission of the media to the device operated by the human subject if the grade level matches or exceeds the lowered threshold level for exclusion. obtaining, by a computing device , a physiological state data as a function of a physical sample; identifying, by the computing device, a user propensity for addictive behavior associated with a human subject as a function of the physiological state data and a behavioral model , wherein the user propensity for addictive behavior identifies an addictive behavior from a predetermined plurality of addictive behaviors; receiving, by the computing device, a media item to be transmitted to a device operated by the human subject; extracting, from the media item, a plurality of media item content elements; classifying each content element of the plurality of media item content elements to a media item object of a plurality of media item objects using an object classifier ; grading the media item with a grade level according to a number of appearances and/or proportion of media item objects associated with the user propensity for addictive behaviour of the plurality of media item objects; blocking transmission of the media to the device operated by the human subject if the grade level matches or exceeds a threshold level for exclusion; receiving, from a remote device , an indication that the human subject has engaged in a problematic behavior associated with the user propensity for addictive behavior; and upon receiving the indication from the remote device: lowering the threshold level; and blocking transmission of the media to the device operated by the human subject if the grade level matches or exceeds the lowered threshold level for exclusion. lowering the threshold level; and blocking transmission of the media to the device operated by the human subject if the grade level matches or exceeds the lowered threshold level for exclusion. <EOS>