Characterising individuals with a substance use disorder accessing hospital‐based addiction care: Preliminary description of the outcomes for patients accessing addiction care prospective cohort study
Bibliographic record
Abstract
INTRODUCTION: Individuals with a substance use disorder (SUD) often face barriers to accessing health care, resulting in unmet needs and delayed care. Hospital-based services have the potential to engage individuals with a SUD in ongoing treatment, but there is limited literature characterising this population. METHODS: The Outcomes for Patients Accessing Addiction Care study was a prospective hospital-based cohort study conducted at St. Paul's Hospital in Vancouver, Canada. Participants were recruited from January 2018 to March 2020. Data were collected through an interviewer-administered questionnaire, including socio-demographic information, substance use history and mental health screening. RESULTS: The cohort included 536 participants, with 31% aged 30-39 years, 63% identifying as White and 74% reporting male sex at birth. Nearly half of the participants were either homeless or living in single room occupancy. Use of substances more than once per week was reported for tobacco/nicotine (86%), marijuana (43%), non-medical use of prescription drugs (29%), illicit stimulants (52%) and illicit opioids (61%). DISCUSSION AND CONCLUSION: This preliminary report provides a description of a hospital-based cohort of individuals with a SUD accessing addiction care. The findings highlight demographic characteristics, mental health issues, substance use patterns and barriers to accessing services. Understanding these factors can inform the development of patient-centred interventions and improve engagement and retention in addiction care. Further research is needed to explore interventions and program effectiveness in this population.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".