Benzodiazepines, antidepressants and addiction: A plea for conceptual rigor and consistency
Bibliographic record
Abstract
The editorial by Jauhar et al. (2019) discusses the recently published concerns about “addiction” to antidepressants (mainly serotonin reuptake inhibitors and serotonin and noradrenaline reuptake inhibitors) in light of an increasing number of publications addressing antidepressant withdrawal symptoms. They (Jauhar et al, 2019) ask a crucial question (“Are antidepressants addictive?”), examine conceptual and methodological issues and arrive at a conclusion that “there is minimal evidence, using established classification systems and concepts, that antidepressants should be classified as addictive substances” (p. 657). We agree with their conclusion that antidepressants are not addictive and that the main argument invoked in support of addiction to antidepressants – the presence of withdrawal symptoms – is not valid. However, we would like to point that the same standard used for antidepressants in this regard should also be applied to other pharmacological agents – to benzodiazepines, in
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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) | 0.001 | 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 | 0.001 |
| 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".