Ketamine-Assisted Psychotherapy for PTSD Related to Racial Discrimination
Bibliographic record
Abstract
Current research suggests that ketamine-assisted psychotherapy has benefit for the treatment of mental disorders. We report on the results of ketamine-assisted intensive outpatient psychotherapeutic treatment of a client with treatment-resistant, posttraumatic stress disorder (PTSD) as a result of experiences of racism and childhood sexual abuse. The client’s presenting symptoms included hypervigilance, social avoidance, feelings of hopelessness, and intense recollections. These symptoms impacted all areas of daily functioning. Psychoeducation was provided on how untreated intergenerational trauma, compounded by additional traumatic experiences, potentiated the client’s experience of PTSD and subsequent maladaptive coping mechanisms. Ketamine was administered four times over a 13-day span as an off-label, adjunct to psychotherapy. Therapeutic interventions and orientations utilized were mindfulness-based cognitive therapy (MBCT) and functional analytic psychotherapy (FAP). New skills were obtained in helping the client respond effectively to negative self-talk, catastrophic thinking, and feelings of helplessness. Treatment led to a significant reduction in symptoms after completion of the program, with gains maintained 4 months post-treatment. This case study demonstrates the effective use of ketamine as an adjunct to psychotherapy in treatment-resistant PTSD.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".