A qualitative study of transgender individuals’ experiences in residential addiction treatment settings: stigma and inclusivity
Bibliographic record
Abstract
BACKGROUND: While considerable research has been undertaken on addiction treatment, the experiences of transgender individuals who use drugs are rarely explored in such research, as too often transgender individuals are excluded entirely or grouped with those of sexual minority groups. Consequently, little is known about the treatment experiences in this population. Thus, we sought to qualitatively investigate the residential addiction treatment experiences of transgender individuals who use illicit drugs in a Canadian setting. METHODS: In-depth semi-structured interviews were conducted with 34 transgender individuals in Vancouver, Canada between June 2012 and May 2013. Participants were recruited from three open prospective cohorts of individuals who use drugs and an open prospective cohort of sex workers. Theory-driven and data-driven approaches were used to analyze the data and two transgender researcher assistants aided with the coding and the interpretation of data in a process called participatory analysis. RESULTS: Fourteen participants had previous experience of addiction treatment and their experiences varied according to whether their gender identity was accepted in the treatment programs. Three themes emerged from the data that characterized individuals' experiences in treatment settings: (1) enacted stigma in the forms of social rejection and violence, (2) transphobia and felt stigma, and (3) "trans friendly" and inclusive treatment. Participants who reported felt and enacted stigma, including violence, left treatment prematurely after isolation and conflicts. In contrast, participants who felt included and respected in treatment settings reported positive treatment experiences. CONCLUSIONS: The study findings demonstrate the importance of fostering respect and inclusivity of gender diverse individuals in residential treatment settings. These findings illustrate the need for gender-based, anti-stigma policies and programs to be established within existing addiction treatment programs. Additionally, it is vital to establish transgender and/or LGBTQ specific treatment programs as recommended by the participants in this study.
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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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.013 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".