Background

Subjective experiences seem to play an important role in the enduring effects of psychedelic experiences. Although the importance of the subjective experience on the impact of psychedelics is frequently discussed, a more detailed understanding of the subtypes of psychedelic experiences and their associated impacts on mental health has not been well documented.
Methods

In the current study, machine learning cluster analysis was used to derive three subtypes of psychedelic experience in a large (n = 985) cross sectional sample.
Results

These subtypes are not only associated with reductions in anxiety and depression symptoms and other markers of psychological wellbeing, but the structure of these subtypes and their subsequent impact on mental health are highly reproducible across multiple psychedelic substances.
Limitations

Data were obtained via retrospective self-report, which does not allow for definitive conclusions about the direction of causation between baseline characteristics of respondents, qualities of subjective experience, and outcomes.
Conclusions

The present analysis suggests that psychedelic experiences, in particular those that are associated with enduring improvements in mental health, may be characterized by reproducible and predictable subtypes of the subjective psychedelic effects. These subtypes appear to be significantly different with respect to the baseline demographic characteristics, baseline measures of mental health, and drug type and dose. These findings also suggest that efforts to increase psychedelic associated personal and mystical insight experiences may be key to maximizing beneficial impact of clinical approaches using this treatment in their patients.