The Clinical Concept of Opioid Addiction Since 1877: Still Wanting After All These Years
Bibliographic record
Abstract
In 1877, the psychiatrist Edward Levinstein authored the first monograph on opioid addiction. The prevalence of opioid addiction prior to his publication had risen in several countries including England, France and Germany. He was the first to call it an illness, but doubted that it was a mental illness because the impairment of volition appeared to be restricted to opioid use: it was not pervasive, since it did not extend to other aspects of the individuals' life. While there has been huge progress in understanding the underlying neurobiological mechanisms, there has been little progress in the clinical psychopathology of addiction and in understanding how it relates to these neurobiological mechanisms. A focus on cravings has limited the exploration of other important aspects such as anosognosia and addiction-related behaviors like smuggling opioids into treatment and supporting the continued provision of co-patients. These behaviours are usually considered secondary reactions, but in clinical practice they appear to be central to addiction, indicating that an improved understanding of the complexity of the disorder is needed. We propose to consider an approach that takes into account the embodied, situated, dynamic, and phenomenological aspects of mental processes. Addiction in this context can be conceptualized as a habit, understood as a distributed network of mental, behavioral, and social processes, which not only shapes the addict's perceptions and actions, but also has a tendency to self-maintain. Such an approach may help to develop and integrate psychopathological and neurobiological research and practice of addictions.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.022 |
| Scholarly communication | 0.005 | 0.010 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.005 | 0.013 |
| Insufficient payload (model declined to judge) | 0.002 | 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".