Implementing psychedelic-assisted therapy: History and characteristics of the Swiss limited medical use program
Bibliographic record
Abstract
This article describes the Swiss limited access program for psychedelic/3,4-methylenedioxymethamphetamine (MDMA)-assisted therapy. The Swiss Federal Office of Public Health can issue authorizations for the limited medical use of otherwise prohibited substances. To be eligible, patients suffer from a mostly incurable disease, the prohibited substance can alleviate the suffering, and there are no alternative treatments, or such treatments have already extensively been used with insufficient outcome. The current program started in 2014 with two physicians. In 2024, there were approximately 100 physicians who held authorizations to treat 723 patients with MDMA (245 patients), lysergic acid diethylamide (130 patients), or psilocybin (348 patients). There were approximately 1660 psychedelic/MDMA-assisted treatments in 2024, with patients typically being treated 2-4 times with the respective substance within 12 months. Various aspects of the program, including its history, provider characteristics and setting, legal requirements, treatment cost, the role of professional societies, education and continuous formation, personal experience, patient characteristics, outcome, and adverse effects, are described and discussed relative to other recently established programs in Canada and Australia. Such information could be of interest to psychedelic-assisted therapy stakeholders, including professionals, patients, and regulatory bodies that are considering setting up similar restricted access programs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".