INJECTION DRUG USE AMONG YOUTH: AN EXPLORATION OF KEY FACTORS INFLUENCING SAFER AND/OR UNSAFE PRACTICES
Bibliographic record
Abstract
Background: Much of the research on injection drug use practices has focused on adult populations and relatively little is known about safer and/or unsafe injection practices among youth who use injection drugs (YWID). Unsafe practices may be risk factors for blood borne illnesses, abscesses or other infections, and overdose. Multiple factors may create barriers to the access of clean supplies and the ability to practice safer injection. It is important to understand how YWID engage in safer and/or unsafe injection practices so that use of safer practices may be supported. \n\nPurpose: The purpose of this study was to explore the understandings and practices of safer and/or unsafe injection drug use among YIWD, as well as key social factors influencing these understandings and practices.\n\nMethods: Ten semi-structured qualitative interviews were conducted with YWID aged 18 to 29 in Halifax, Nova Scotia. Voluntary informed consent was obtained prior to conducting the interviews. All interviews were audio-taped and transcribed, then analyzed using a modified approach to grounded theory for key themes and subthemes.\n\nResults: The experiences of the YWID can be categorized into two overarching themes. The first theme relates to the power of the drugs and the control (or, at times, lack of control) YWID have over safer practices. This theme explores how access to clean supplies and understandings of safer use can influence the control YWID have over safer practices. The second theme describes experiences YWID have with “getting clean,” or gaining power over drugs, including experiences with methadone maintenance treatment.\n\nDiscussion: YWID can and do practice safer use, however multiple factors, such as the perception of cleanliness in injection practices and the availability of clean needles in the community, impact how YWID understand and practice safer injection drug use. Barriers that impede YWID’s ability to practice safer use need to be addressed.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".