Nonmedical prescription psychiatric drug use and the darknet: A cryptomarket analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Nonmedical prescription psychiatric drug use (NMPDU) is an increasing global health problem, with recent concern focusing on darknet cryptomarkets as sources of procurement. There is a shortage of evidence regarding comparative worldwide NMPDU trends, due in part to data collection difficulties. This problem is particularly marked for non-opioid drugs, particularly those psychiatric drugs which act on the central nervous system (CNS) and have high misuse potential and are associated with high levels of dependency and fatal overdose. This paper therefore has two goals: 1) to report on the kinds of psychiatric prescription drugs available on cryptomarkets, and 2) to use this data to uncover temporal and geographical trends in sales of these products, potentially informing policy regarding NMPDU more generally. METHOD: Digital trace data collected from 31 cryptomarkets in operation between September 2013 and July 2016 was analysed by country of origin descriptively and for trends in the sales for 7 psychiatric drug groupings, based on their main indication or intended use in psychiatric practice. RESULTS: Sedatives (such as diazepam and alprazolam) and CNS stimulants (mainly Adderall, modafinil and methylphenidate) had the greatest share of sales, but usage and trends varied by location. The UK has high and rising levels of sedative sales, whilst the USA has the greatest stimulant sales and increasing sedative rates. Sales of drugs used in the treatment of opioid dependency are also substantial in the USA. The picture is less clear in mainland Europe with high sales levels reported in unexpected Central and Northern European countries. There is evidence of a move towards the more potent sedative alprazolam - already implicated as a source of problematic NMPDU in the USA - in Australia and the UK. Sales of drugs such as antidepressants, antipsychotics, mood stabilisers and antidementia drugs - all drugs with limited abuse potential - were negligible, indicating minimal levels of online cryptomarket procurement for self-medicating mental health problems. CONCLUSION: Predominantly, psychiatric drugs with potent sedative, stimulant or euphoriant effects are sold on cryptomarkets and this varies by country. With some caveats regarding the limitations of cryptomarket digital trace data taken into account, the study of trends of these products sold online over time may offer a novel and increasingly important window onto wider drug purchasing habits.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 it