Social and structural determinants of injection drug use-associated bacterial and fungal infections: a qualitative systematic review and thematic synthesis
Bibliographic record
Abstract
ABSTRACT Background Injection drug use-associated bacterial and fungal infections are increasingly common, and social contexts shape individuals’ injecting practices and treatment experiences. We sought to synthesize qualitative studies of social-structural factors influencing incidence and treatment of injecting-related infections. Methods We searched PubMed, EMBASE, Scopus, CINAHL, and PsycINFO from January 1, 2000, to February 18, 2021. Informed by Rhodes’ “risk environment” framework, we performed thematic synthesis in three stages: (1) line-by-line coding; (2) organizing codes into descriptive themes, reflecting interpretations of study authors; (3) consolidating descriptive themes into conceptual categories to identify higher-order analytic themes. Results We screened 4,841 abstracts and included 26 qualitative studies on experiences of injecting-related bacterial and fungal infections. We identified six descriptive themes organized into two analytic themes. The first analytic theme, social production of risk , considered macro-environmental influences. Four descriptive themes highlighted pathways through which this occurs: (1) unregulated drug supply , leading to poor drug quality and solubility; (2) unsafe spaces , influenced by policing practices and insecure housing; (3) health care policies and practices , leading to negative experiences that discourage access to care; and (4) harm reduction programs , including structural barriers to effective service provision. The second analytic theme, practices of care among people who inject drugs , addresses protective strategies that people who inject drugs employ within infection risk environments. Associated descriptive themes were: (5) mutual care , including assisted-injecting and sharing sterile equipment; and (6) self-care , including vein health and self-treatment. Within constraining risk environments, some protective strategies for bacterial infections precipitated other health risks (e.g., HIV transmission). Conclusions Injecting-related bacterial and fungal infections are shaped by modifiable social-structural factors, including unregulated drug quality, criminalization, insufficient housing, limited harm reduction services, and harmful health care practices. Enabling environment interventions that address these factors could further empower people who inject drugs to protect themselves and their community.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.062 | 0.105 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.020 | 0.026 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.002 | 0.001 |
| 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".