The landscape of ketamine use disorder: Patient experiences and perspectives on current treatment options
Bibliographic record
Abstract
AIMS: To report the symptoms and aetiology of ketamine use disorder (KUD), gauge the effectiveness of current treatment services and identify strategies to enhance patient access and outcomes. DESIGN: Mixed-methods, cross-sectional questionnaire. Electronic survey from November 2023 to April 2024. SETTING: Participants were recruited through snowball sampling, social media and referrals from UK addiction treatment services. The survey was open to international participants, with responses collected from the United Kingdom, United States, Canada, Europe and Australia. PARTICIPANTS/CASES: A total of 274 individuals with self-identified KUD, including both treatment-seeking (40%) and non-treatment-seeking (60%) current or former ketamine users. Participants' ages ranged from 18 to 67 years old, with 47.7% identifying as male. Additionally, 58.8% reported a diagnosed mental health disorder. On average, participants consumed 2.0 g of ketamine per day, with treatment-seeking individuals reporting higher average use (M = 2.67 g) than non-treatment-seeking users (M = 1.68 g) (P < 0.001). MEASUREMENTS: Participants completed an online questionnaire addressing their attitudes toward ketamine and treatment services, including questions pertaining to their symptoms of problematic ketamine use, perceptions of education and awareness about KUD, opinions of existing treatment options, and facilitators for seeking treatment. FINDINGS: The study identified various physical symptoms associated with KUD, with bladder problems (60%), nasal problems (60%) and 'K-cramps' (56%) being commonly reported among all users. In response to these symptoms, the majority (56%) did not seek treatment; among treatment-seeking users only 36% reported feeling satisfied with their care. Symptoms of abstinence syndrome were also identified, including cravings (71%), low mood (62%), anxiety (59%) and irritability (45%). Treatment-seeking participants reported that the services they used had little (31%) or some (31%) awareness of ketamine, were not tailored to ketamine use (43%) and were generally only somewhat effective (43%). Fifty-nine percent of participants reported that there was "definitely not" sufficient awareness in education and peer groups about the risks associated with ketamine use. When asked about the most important factors when choosing a treatment program, cost/affordability was the most cited for all participants. CONCLUSIONS: Ketamine use disorder (KUD) appears to be associated with a high prevalence of physical and psychological symptoms, including some specifically linked to abstinence. Despite this, most individuals with KUD do not seek treatment, and existing services are often perceived as ineffective.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".