Integrating psychotherapy and psychopharmacology: psychedelic-assisted psychotherapy and other combined treatments
Bibliographic record
Abstract
INTRODUCTION: Combinations of psychotherapy with antidepressants are gold-standard psychiatric treatments. They operate through complex and interactional mechanisms, not unlike the reemergent paradigm of psychedelic-assisted psychotherapy, which promising research suggests may also be highly effective in even challenging populations. AREAS COVERED: We review the therapeutic mechanisms behind both conventional and psychedelic paradigms, including the evolution of this knowledge and the associated explanatory frameworks. We explore how psychedelics have provided insights about psychiatric illnesses and treatments over the past decades. We discuss limitations to early explanatory models while highlighting and comparing the psychological and biological mechanisms underlying many psychiatric treatments. METHODS: , 2020, and iterative retrieval of references from recent reviews and clinical trials. EXPERT OPINION: The contextual model of the common factors of psychotherapy provides a powerful perspective on psychotherapy, antidepressants, and psychedelics, as well as 3,4-methylenedioxymethamphetamine (MDMA) and ketamine. It aligns well with key tenets of psychedelic-assisted psychotherapy. Conventional antidepressants and especially psychedelics may improve the efficacy of psychotherapy via neurochemical changes and increased environmental sensitivity. Combined treatments hold significant promise for advancing the knowledge and treatment of many forms of psychopathology.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".