Characterization of a Cohort of Persons Who Use Methamphetamines in London, Ontario, and In-hospital Substance Use
Bibliographic record
Abstract
ABSTRACT Our objective was to describe the sociodemographic characteristics of a cohort of people who use methamphetamine with a history of hospitalizations in London, Ontario, including their substance use patterns, health and social service use patterns, and self-perceived quality of life. Participants were recruited from community and hospital settings in Southwest Ontario, and survey data were collected between October 2020 and May 2021. A total of 109 individuals were recruited in the study, of whom 32.1% reported a hospitalization directly related to methamphetamine use and 55.0% reported using substances during a hospitalization. The survey participants had high rates of health and social service use, as well as emergency department visits. Scores for quality of life and community integration were lower for the study participants compared with general population scores. We found that in-hospital substance use was higher than reported previously, highlighting the need to address this issue to support people who use methamphetamine in the hospital setting. Notre objectif était de décrire les caractéristiques sociodémographiques d’une cohorte de personnes consommant de la méthamphétamine et ayant des antécédents d’hospitalisation à London, en Ontario, incluant leurs habitudes de consommation de substances, leurs habitudes d’utilisation des services sociaux et de santé et leur perception de leur qualité de vie. Les participants ont été recrutés dans les milieux communautaires et hospitaliers du sud-ouest de l’Ontario, et les données de l’enquête ont été recueillies entre octobre 2020 et mai 2021. Au total, 109 personnes ont été recrutées dans l'étude. 32,1% ont déclaré une hospitalisation directement liée à la consommation de méthamphétamine, et 55,0% ont déclaré avoir consommé des substances pendant une hospitalisation. Les participants à l’enquête présentaient des taux élevés d’utilisation des services sociaux et de santé, ainsi que de visites aux urgences. Les scores de qualité de vie et d’intégration dans la communauté étaient inférieurs pour les participants à l'étude par rapport aux scores de la population générale. Nous avons constaté que la consommation de substances à l’hôpital était plus élevée que ce qui avait été rapporté précédemment, ce qui souligne la nécessité d’aborder cette question pour soutenir les personnes qui consomment de la méthamphétamine en milieu hospitalier.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".