One Ultimate Journey? AKA the Huxley’s Method: Perspectives of (Ab)Users of Hallucinogens and Entheogens on Having Planned Pre-Mortem Psychedelic Trip | Al-Imam | Modern Applied Science | CCSE

Background: The surface web is a rich source of extensive data on populations of users and misusers of psychoactive substances including substances known as hallucinogens and entheogens. The internet and its social media websites can serve as a database upon which several hypotheses are applicable via thematic analytic and psychoanalytic studies. Materials and Methods: This study will deploy the use of an internet snapshot by inspecting, via thematic analysis, the comments of a population of psychedelic (ab)users existing on the Facebook social platform. The snapshot will dare to answer an existing question in connection with the concept of using psychedelics and entheogens during the moments preceding death. Several demographics will be explored including ethnic-national and socio-cultural parameters to test several hypotheses about the tendencies for having an ultimate pre-mortem psychedelic trip towards the ambiguous afterlife. Results: Most of the psychedelic users recommended the use of DMT for the final journey. Others have suggested tripping on LSD, Psilocybin and Psilocybin mushrooms, NBOMe compounds, and even opiates. Based on inferential models, it seems that tendencies for the pre-mortem trip are not affected by the status of social relations, ethnicity, nationality, age, or sex. However, it appears to be based on the individualistic build-up. Religious affiliations and other cultural norms represent potential confounding variables. Hence, these must be explored in subsequent studies. Conclusion: In the future and to keep in pace with the logarithmic growth and arachnoid expansion of the web and its appendages, ambitious studies has to deploy the use of concepts of automation in data science via the exploitation of principles of machine learning and deep thinking. The aim is to achieve statistical inference in real-time and accurate predictions when it comes to running analytics on big data. If successfully applied, the benefits for the public health should be monumental