Addiction chronicity: are all addictions the same?
Bibliographic record
Abstract
Background All addictions have a recurring nature, but their comparative chronicity has never been directly investigated. The purpose of this study is to undertake this investigation.Method A secondary analysis was conducted on two large scale 5-year Canadian adult cohort studies. A subset of 1,088 individuals were assessed as having either substance use disorder, gambling disorder, excessive behaviors (e.g. shopping, sex/pornography), or two or more of these designations (‘multiple addictions’) during the course of these studies. Within each dataset comparisons were made between these four groups concerning the number of waves they had their condition; likelihood of having their condition in two or more consecutive waves; and likelihood of relapse following remission.Results Multiple addictions had significantly greater chronicity on all measures compared to single addictions. People with an excessive behavior designation had significantly lower chronicity compared to people with gambling disorder and a tendency toward lower chronicity compared to substance use disorder. Gambling disorder had equivalent chronicity to substance use disorder in one dataset but greater chronicity in the other. However, this latter difference is likely an artifact of the different time frames utilized.Conclusions Having multiple addictions represents a more pervasive condition that is persistent for most individuals. Substance use disorder and gambling disorder have intermediate and roughly equivalent levels of chronicity, but considerable individual variability, transient for some, but more chronic for others. In contrast, excessive behaviors such as compulsive shopping are transient for most, and their comparatively lower levels of chronicity questions their designations as ‘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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".