The chronic disease concept of addiction: Helpful or harmful?
Bibliographic record
Abstract
In contemporary culture, socially deviant behaviour is increasingly being conceptualised as the result of a disease; most salient perhaps, in regards to addiction. This chronic disease model of alcoholism has its roots in early assumptions that have recently been discredited or at least challenged. This study employs an experimental method to examine whether telling individuals with a mild to moderate alcohol addiction that they have a chronic brain disease influences their perceptions of addiction-related agency as well as their feelings of shame and stigma. Participants, recruited online, were randomly assigned to internalise statements promoting (a) a disease model of addiction, (b) a psychosocial model or (c) a neutral control condition; they then completed several indices of agency in relation to drinking, as well as measures of stigma and shame. Participants who internalised the disease model of addiction tended to have weaker perceptions of drinking self-efficacy, whereas internalising psychosocial model beliefs tended to induce a stronger internal locus of control and weaker entitisation of addiction. Both the disease and the psychosocial conditions increased, in comparable amounts, feelings of stigma and shame relative to the control condition. This study provides empirical support to the notion that framing addiction within a biological conceptualisation, as opposed to a psychological and social framework, weakens perceptions of agency in relation to drinking. Likewise, no evidence was found to support the common assertion that the disease model reduces feelings of stigma and shame.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.013 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| 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".