Risk Factors Associated With In-hospital Substance Use Among People Who Use Methamphetamine in London, Ontario
Bibliographic record
Abstract
ABSTRACT In this secondary analysis, our objective was to identify risk factors for in-hospital substance use among people with a history of methamphetamine use and hospitalization in London, Ontario. Survey data from a total of 109 participants were collected between October 2020 and May 2021. Among our sample, 55.0% reported using substances during a hospitalization. Factors significantly associated with using substances while hospitalized included self-reported attention-deficit hyperactivity disorder (ADHD) [OR=3.15 (1.13, 8.77)], and accessing a social or medical service in the past six months [OR=2.26 (1.02, 4.99)]. In the multivariable model, factors significantly associated with using substances while hospitalized included white race [OR=3.24 (1.24, 8.45)], and self-reported ADHD [OR=3.98 (1.07, 14.8)]. We report a novel association between in-hospital substance use and ADHD, a common comorbidity associated with methamphetamine use. Identifying risk factors associated with in-hospital substance use is important in designing appropriate policies to prevent potential harm related to substance use during hospitalization. Dans cette analyse secondaire, notre objectif était d’identifier les facteurs de risque de consommation de substances à l’hôpital chez les personnes ayant des antécédents de consommation de méthamphétamine et ayant été hospitalisées à London, en Ontario. Les données d’enquête ont été collectées auprès d’un total de 109 participants entre octobre 2020 et mai 2021. Parmi notre échantillon, 55,0% ont déclaré avoir consommé des substances lors d’une hospitalisation. Les facteurs significativement associés à la consommation de substances lors d’une hospitalisation comprenaient le trouble déficitaire de l’attention avec hyperactivité (TDAH) déclaré (OR=3,15 [1,13 ; 8,77]), ainsi que l’accès à un service social ou médical au cours des six derniers mois (OR=2,26 [1,02 ; 4,99]). Dans le modèle multivariable, les facteurs significativement associés à la consommation de substances pendant l’hospitalisation comprenaient la race blanche (OR=3,24 [1,24-8,45]) et le TDAH déclaré (OR=3,98 [1,07-14,8]). Nous rapportons une nouvelle association entre la consommation de substances à l’hôpital et le TDAH, une comorbidité courante associée à la consommation de méthamphétamine. L’identification des facteurs de risque associés à la consommation de substances psychoactives en milieu hospitalier est importante pour concevoir des politiques appropriées visant à prévenir les dommages potentiels liés à la consommation de substances psychoactives au cours d’une hospitalisation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".