Medicinal psychedelics for mental health and addiction: Advancing research of an emerging paradigm
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The medical use of psychedelic substances (e.g. psilocybin, ayahuasca, lysergic acid diethylamide and 3,4-methylenedioxymethamphetamine) is attracting renewed interest, driven by a pressing need for research and development of novel therapies for psychiatric disorders, as well as promising results of contemporary studies. In this Viewpoint, we reflect upon the ‘Clinical Memorandum on Psychedelics’ recently released by the Royal Australian and New Zealand College of Psychiatrists and note subsequent developments including the application for down-scheduling of psilocybin and 3,4-methylenedioxymethamphetamine presently being considered by the Therapeutic Goods Administration and approvals for access via the Special Access Scheme. We suggest that this field is worthy of rigorous research to assess potential benefits, address safety parameters and clarify therapeutic mechanisms. To this end, we outline recent research findings, provide an overview of current knowledge relating to mechanisms of action and discuss salient aspects of the psychedelic-assisted psychotherapy treatment model. The sum of this research points towards medicinal psychedelics as a potential new class of psychiatric treatments when used within a medically supervised framework with integrated psychotherapeutic support. However, before widespread translation into clinical use can occur, appropriately designed and sufficiently powered trials are required to detect both potential positive and negative outcomes. Unique safety and regulatory challenges also need to be addressed. As for any new medical therapy, psychedelic research needs to be conducted in a rigorous manner, through the dispassionate lens of scientific enquiry. Carte blanche availability to practitioners, without specific protocols and appropriate training, would be potentially harmful to individuals and detrimental to the field.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it