Ethnoracial Inclusion in Clinical Trials of Ketamine in the Treatment of Mental Health Disorders
Bibliographic record
Abstract
OBJECTIVE: Despite strong evidence for the safety and efficacy of ketamine in the treatment of mood disorders, the enrollment of Black, Indigenous, and People of Color (BIPOC) has not been a focus of this research. Health disparities in the treatment of mood disorders in BIPOC indicate a strong need to understand the clinical, social, and pharmacological aspects of this novel treatment in people of color. METHOD: A comprehensive methodological search for double-blind, placebo-controlled, randomized ketamine clinical trials published from 1993 to 2020 was conducted across several databases to analyze the demographics of trial participants. Researchers contacted corresponding authors to obtain additional information. RESULTS: = 380 participants), 73.7% of the participants were non-Hispanic White, 9.2% were Black, 5.0% were Hispanic/Latinx, and 0.8% were Asian. Higher BIPOC inclusion was negatively correlated with the number of recruitment methods implemented across sites. The present study may underestimate the participation of BIPOC because of the lack of demographic information collected or published. CONCLUSIONS: BIPOC are greatly underrepresented in ketamine clinical trials despite high rates of mood disorders. Reported treatment outcomes may not generalize to all ethnic and cultural groups and significant disparities in access to such novel treatment paradigms exacerbate health disparities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 teacher head, 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".