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Record W2914900797 · doi:10.1111/add.14560

Commentary on Degenhardt <i>et al</i>. (2019): Harm to others matters in substance use disorders, and so does discordance between the diagnostic systems

2019· letter· en· W2914900797 on OpenAlexaff
Robin Room, Jürgen Rehm

Bibliographic record

VenueAddiction · 2019
Typeletter
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsPublic Health OntarioUniversity of TorontoCentre for Addiction and Mental Health
Fundersnot available
KeywordsHarmAddictionPsychologyPsychiatrySubstance usePrestigeSubstance abuseSocial psychology

Abstract

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Re-examining items analysed by Degenhardt and colleagues points to harm to others as an important constituent of substance use disorders in surveys, as in clinical realities. The study finds a substantial divergence between ICD-11 and DSM-5 in what constitutes a case in substance use disorders. As Degenhardt and colleagues 1 indicate, the psychiatric tradition had decided by the 1960s that addiction was the main game with respect to psychoactive substances, but renamed it ‘dependence’, in part seeking the greater prestige of the physiological phenomena of tolerance and withdrawal, from which the term was adapted 2; but however it was named, the primary location of the disorder was defined as in the mind of the user, and anything used as an indicator was conceptually subordinated to the mental urges and ambivalences of the user. This is reflected in the key phrases cited by Degenhardt and colleagues from the questionnaire items to measure aspects of dependence. Thus, for instance, ‘problems with family, friends or others’ are subordinated to ‘continued use despite it causing’ the problems, so the item is classified as measuring one of the criteria for dependence, ‘substance use becomes an increasing priority in life’. The Platonism in interpreting the items makes one of the paper's conclusions from its analysis quite problematic. The paper interprets the item: ‘family been hurt by your substance use’ as its measurement of harm to others, and finds that few answered ‘yes’ to it, so that it did not add substantially to overall rates. However, this ignores that harm to others is quite widely referred to or implied in other questionnaire items in the surveys; not only the item already mentioned but also items classified under ‘harmful use’, such as ‘interfered frequently with your work or other responsibilities at school, on a job, or at home’ and that the use ‘resulted in problems with the police’. Re-classifying all relevant items as indications of harm to others from the substance use would considerably increase the weight of this aspect in the ICD-11 diagnosis. The aspect contributes to the clinical utility of the diagnosis, as harm to others is an important determinant of which substance users become ‘cases’ to be treated and managed, as reflected in the commonplace that those who come to treatment in alcohol and drug treatment services are more often than not being pushed in the door by others, whether formally or informally 3. All in all, Degenhardt and colleagues’ conclusion questioning the diagnostic validity of self-reported ‘harm to others’ does not seem justified. At a more general level, the data and findings in their paper 1 alert us to implications of the radical split between diagnostic systems which ICD-11 and DSM-5 embody. ICD-11 has continued the distinction between dependence, on one hand, and harmful use on the other hand. DSM-5 has abandoned any distinction; all symptoms are now equal indications of ‘use disorder’; dependence has officially gone, but often is inferred indirectly by severity as measured by the number of items indicating a disorder. The paper's results demonstrate that the two systems also arrive at different conclusions about whether an individual case has a disorder: in Table 6, of the cases where any disorder is found, it is found by only one of the systems for 36% of the alcohol cases and for 46% of the cannabis cases. In the new era, the two diagnostic systems disagree not only on concepts but also on what constitutes ‘a case’. It is not clear what this means for treatment. In many countries, especially for alcohol, most cases never receive treatment, and those treated may not qualify to be a psychiatrically defined case 4. Thus, the diagnostic definitions and surveys seem to exist in a somewhat different world from the social realities, including within treatment systems. From a population-based public health perspective, we need to reconsider what makes the most sense as indicators of substance use-induced hazard or harm. Dependence turns out to be a somewhat culture-specific concept 5, 6, with different regions of the world showing quite different relationships between amount of drinking and reported alcohol dependence rates 7. There are two alternative bases for population-level indicators. One option is levels and patterns of consumption 8. The other is a cumulative indicator of substance-use related harm, whether to the user or to others—as in ICD-11's harmful use, or in traditions of population studies of alcohol and other drug problems (e.g. 9. In trying to determine what is most useful at a population level (although not necessarily in a clinical situation), perhaps it is time to look beyond interpretations and diagnoses which privilege what is in the user's mind, instead taking items about substance-induced harm at their face value and focusing on reducing them. R.R. and J.R. have both served as consultants and advisers to the World Health Organization, including on the diagnosis and classification of substance use disorders, for many years. The opinions expressed here are personal, and not ascribable to WHO. They report no other conflicts of interest.

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)
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 score0.178
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.014
GPT teacher head0.253
Teacher spread0.239 · 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

Citations8
Published2019
Admission routes1
Has abstractyes

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