“They look at us like junkies”: influences of drug use stigma on the healthcare engagement of people who inject drugs in New York City
Bibliographic record
Abstract
BACKGROUND: People who inject drugs (PWID) are a medically and socially vulnerable population with a high incidence of overdose, mental illness, and infections like HIV and hepatitis C. Existing literature describes social and economic correlations to increased health risk, including stigma. Injection drug use stigma has been identified as a major contributor to healthcare disparities for PWID. However, data on this topic, particularly in terms of the interface between enacted, anticipated, and internalized stigma, is still limited. To fill this gap, we examined perspectives from PWID whose stigmatizing experiences impacted their views of the healthcare system and syringe service programs (SSPs) and influenced their decisions regarding future medical care. METHODS: Semi-structured interviews conducted with 32 self-identified PWID in New York City. Interviews were audio recorded and transcribed. Interview transcripts were coded using a grounded theory approach by three trained coders and key themes were identified as they emerged. RESULTS: A total of 25 participants (78.1%) reported at least one instance of stigma related to healthcare system engagement. Twenty-three participants (71.9%) reported some form of enacted stigma with healthcare, 19 participants (59.4%) described anticipated stigma with healthcare, and 20 participants (62.5%) reported positive experiences at SSPs. Participants attributed healthcare stigma to their drug injection use status and overwhelmingly felt distrustful of, and frustrated with, medical providers and other healthcare staff at hospitals and local clinics. PWID did not report internalized stigma, in part due to the availability of non-stigmatizing medical care at SSPs. CONCLUSIONS: Stigmatizing experiences of PWID in formal healthcare settings contributed to negative attitudes toward seeking healthcare in the future. Many participants describe SSPs as accessible sites to receive high-quality medical care, which may curb the manifestation of internalized stigma derived from negative experiences in the broader healthcare system. Our findings align with those reported in the literature and reveal the potentially important role of SSPs. With the goal of limiting stigmatizing interactions and their consequences on PWID health, we recommend that future research include explorations of mechanisms by which PWID make decisions in stigmatizing healthcare settings, as well as improving medical care availability at SSPs.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".