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BREAKING UP WITH YOUR DRUG CAN BE HARD TO DO, BUT IS IT MAINLY BECAUSE COMPULSIVE BEHAVIOR INVOLVES SPECIFIC BRAIN REGIONS?

2004· letter· en· W1843441311 on OpenAlexaboutno aff
Lynn T. Kozlowski, Beth Edwards

Bibliographic record

VenueAddiction · 2004
Typeletter
Languageen
FieldNeuroscience
TopicNeurotransmitter Receptor Influence on Behavior
Canadian institutionsnot available
Fundersnot available
KeywordsAddictionTerminologyPsychologyDrugPsychological dependencePsychiatryPhysical dependenceMedicinePharmacology

Abstract

fetched live from OpenAlex

Reading Lubman et al. (2004) stirred a memory. Years ago, The Royal Society of Canada convened a committee at the request of Health and Welfare Canada to consider whether nicotine in cigarettes was addictive (Kalant et al. 1989). Fortunately the chair of this committee was the distinguished Harold Kalant who had the experience of decades of working on prominent international committees (e.g. for the World Health Organization) concerned with the definition of drug dependence and addiction. (LTK also served on this RSC committee). The beginning of this report benefited especially from Kalant's experience with historical changes in terminology and definitions. It was judged that ‘Earlier definitions of drug addiction have evolved over the past 40 years, in the direction of diminishing emphasis on tolerance and physical dependence as defining features of addiction, and growing emphasis on the behavioural aspects of “compulsive” drug-seeking and drug-taking, reinforced by the psychoactive effects of the drug, and on the great difficulty in cessation of drug-taking and the high probability of relapse’ (p. v). The definition was: Drug addiction is a strongly established pattern of behaviour characterized by (1) The repeated self-administration of a drug in amounts which produce reinforcing psychoactive effects, and (2) great difficulty in achieving voluntary long-term cessation of such use, even when the user is strongly motivated to stop. (p. v) This definition might be shortened to: ‘a drug use that is difficult to stop.’ Part of our intent was to avoid terms like ‘withdrawal’, ‘psychological dependence’, and ‘physical dependence’ because of their unclear relationship to the underlying fact of difficulty in stopping. At the time we expressed reluctance to employ the ‘imprecise and mechanistically questionable term “compulsive.”’ Now, almost 15 years later, developments in brain imaging and neuroscience and progress in research on obsessive-compulsive disorder may have increased precision and have made it less questionable to explore what it means to say that addiction is a form of compulsive behavior, and there may be a promising idea of which brain regions are involved. In pursuing this program of research we would ask for more work to clarify what comes first—the addictive behavior or the brain dysfunction. We would also encourage a re-reading of an even older paper in addiction research. Did Lee Robins’ famous US soldiers who were addicted to heroin in Vietnam, but not when they returned home, have their brains (now their prefrontal cortexes) hi-jacked in South-East Asia, but freed in the US (Robins 1973)? Would longitudinal studies of changes in inhibitory brain dysfunction in these soldiers have helped explain this effect or were broader ecological issues more likely at play? Advancing our understanding of addiction will probably benefit from models that include measures of context as well as brain.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.365
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.069
GPT teacher head0.295
Teacher spread0.226 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreCommentary

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".

Quick stats

Citations1
Published2004
Admission routes1
Has abstractyes

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