J Affect Disord
April 1, 2018
Facundo Carrillo, Mariano Sigman, Diego Fernández Slezak et al.
57 citations
An algorithm analyzing natural speech from baseline interviews can predict which patients with treatment-resistant depression will respond to psilocybin therapy. The approach uses vocal patterns and linguistic features to forecast treatment outcomes, suggesting that speech biomarkers may enable personalized medicine in mental health. This predictive capability could help identify likely responders before treatment begins, advancing precision psychiatry for depression.
Journal of Psychedelic Studies
September 16, 2022
Ada Kałużna, Marco Schlosser, Emily Gulliksen Craste et al.
41 citations
Both ego-dissolution and connectedness during a psychedelic experience are associated with a higher chance of therapeutic improvement, but they affect people differently. Ego-dissolution tends to trigger psychological change that typically does not last beyond the psychedelic experience, while connectedness can be more sustained and is linked to several positive, potentially therapeutic feelings. A mixed-methods systematic review of 15 studies (2,182 participants) synthesized findings from four databases. The results suggest that emphasizing ego-dissolution during preparation and connectedness during integration may improve psychedelic therapy models, with broader implications for mental health practice.
Psychopharmacology
February 1, 2025
Jack Stroud, Charlotte Rice, Aaron Orsini et al.
8 citations
The majority of autistic participants who completed an online survey reported that their most impactful psychedelic experience reduced psychological distress (82%) and social anxiety (78%) and increased social engagement (70%). A substantial minority (20%) reported undesirable effects such as increased anxiety, with some describing the experience as among the most negatively impactful of their lives. The only substantial predictor of reduced distress was increased psychological flexibility. The findings come from a non-experimental design with biased sampling, so caution is warranted.
medRxiv
August 28, 2024
Zishan Jiwani, Simon B. Goldberg, Jack Stroud et al.
3 citations
preprint
Most meditators who use psychedelics perceive them as beneficial for their meditation practice. Among 863 regular meditators (practicing at least three times weekly for the past year) who also used psychedelics, machine learning identified four factors most likely to predict this positive perception: greater frequency of psychedelic use, setting intentions before use, higher agreeableness, and having used N,N-Dimethyltryptamine (DMT). The model explained about 27% of the variance. The findings suggest that intentional and personality factors may shape how psychedelics influence meditation, but causality remains unestablished.
PLoS One
February 12, 2025
Zishan Jiwani, Simon B. Goldberg, Jack Stroud et al.
1 citation
Most meditators who also use psychedelics report that the drugs improve their meditation practice. In a survey of 863 regular meditators who had used psychedelics, 73.5% said psychedelics positively influenced the quality of their meditation. Machine learning analysis of 53 variables identified the strongest predictors of this perceived benefit: greater frequency of psychedelic use, setting intentions before taking psychedelics, having an agreeable personality, and having used N,N-Dimethyltryptamine (N,N-DMT). The results suggest that individual traits and patterns of use shape whether psychedelics are seen as helpful for meditation, but causality cannot be established from this cross-sectional data.