Use of a Synthetic Cannabinoid in a Correctional Population for Posttraumatic Stress Disorder–Related Insomnia and Nightmares, Chronic Pain, Harm Reduction, and Other Indications
Bibliographic record
Abstract
Nabilone is a synthetic cannabinoid that has shown promise for the treatment of posttraumatic stress disorder (PTSD)-related insomnia and nightmares as well as efficacy in the management of chronic pain. It has also been proposed for harm reduction in cannabis dependence. Its effectiveness for management of concurrent disorders in seriously mentally ill correctional populations has not been evaluated. This retrospective study of 104 male inmates with serious mental illness prescribed nabilone analyzes the indications, efficacy, and safety of its use. Medications discontinued with the initiation of nabilone were also reviewed. The results showed nabilone targeting a mean of 3.5 indications per patient, thus likely reducing polypharmacy risk. The mean final dosage was 4.0 mg. Results indicated significant improvement in PTSD-associated insomnia, nightmares, PTSD symptoms, and Global Assessment of Functioning and subjective improvement in chronic pain. Medications associated with greater risk for adverse effects or abuse than nabilone were often able to be discontinued with the initiation of nabilone, most often antipsychotics and sedative/hypnotics. There was no evidence of abuse within this high-risk population or reduction of efficacy when nabilone was given in powder form with water rather than as a capsule. This study supports the promise of nabilone as a safe, effective treatment for concurrent disorders in seriously mentally ill correctional populations. Prospective, randomized controlled trials are required to confirm our preliminary results. Follow-up in the community will be required to confirm effectiveness in harm reduction.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".