Cognitive outcomes following psilocybin-assisted therapy in treatment-resistant depression: A post-hoc analysis of a randomized, waitlist-controlled trial
Bibliographic record
Abstract
BACKGROUND: Cognitive difficulties within treatment-resistant unipolar and bipolar depression (TRD; TRBD) often do not improve with conventional pharmacotherapies. Psilocybin-assisted psychotherapy (PAP) has shown promise as a novel intervention for TRD; however, few studies have assessed its effects on cognition in this population. METHODS: This retrospective post hoc analysis included 26 adults with TRD or TRBD from an open-label trial of PAP. Cognition was assessed with the Digit Symbol Substitution Test (DSST) and Trail Making Test Part A and B (TMT-A/B) at baseline, one-day, and two-weeks post-treatment. Linear mixed models (LMMs) evaluated change over time, and reliable change indices (RCIs) with binomial tests assessed whether the proportion of participants showing meaningful improvement exceeded chance. RESULTS: Significant improvements were observed on all cognitive measures over time (all p < .05). After adjusting for depressive symptoms, gains on the TMT-A (p < .001), TMT-B (p < .001), and TMTB - A (p = .005) remained significant. In contrast, DSST improvements were attenuated (p = .069). RCIs showed that 4.2 %-12.5 % of participants achieved meaningful improvement, but these rates did not significantly exceed chance expectations. CONCLUSION: PAP was associated with modest, short-term improvements in performance on measures of processing speed and executive function among individuals with TRD. While these changes appeared independent of mood, they did not consistently exceed expected practice effects. These findings highlight the need for adequately powered, controlled trials to clarify whether observed cognitive changes reflect genuine procognitive effects of psilocybin or are attributable to non-specific influences such as test familiarity or concurrent mood improvements.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.004 | 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".