Transgender and Gender Diverse People's Experiences of Acute and Post-Discharge Mental Healthcare in Ontario: A Mixed Methods Study
Bibliographic record
Abstract
Introduction: Transgender (trans) and gender diverse (TGD) people experience significant oppression, which can translate into greater risk of mental disorders and need for acute mental healthcare, i.e. mental health hospitalizations and emergency department (ED) visits. Early post-discharge care can reduce negative health outcomes following acute care presentations. The aim of this study was to understand TGD people’s experiences of acute and post-discharge mental healthcare. Objectives: 1) To compare characteristics of TGD and non-TGD individuals accessing acute mental healthcare 2) To compare physician visits following discharge from acute psychiatric care (mental health-related ED visits or hospitalizations) between TGD and non-TGD individuals 3) To explore the lived experiences of TGD people accessing acute mental healthcare and understand their post-discharge journeys 4) To integrate the qualitative and quantitative data to explain the quantitative results Methods: A sequential explanatory mixed methods study was conducted. First, a retrospective population-based cohort study used linked health administrative data to examine psychiatric patients discharged from an ED visit or hospitalization in Ontario, Canada. TGD individuals were identified and their data linked with health administrative data. Sociodemographic and clinical factors associated with the TGD ED and hospitalization samples were examined. Multivariable logistic regression analyses examined outpatient mental health physician follow-up within 30 days of discharge. The quantitative results guided the subsequent qualitative study design and data generation plan. TGD people living in Toronto, Ontario, who have experienced acute mental healthcare (n = 15) were recruited for the qualitative study. In-depth individual interviews were conducted, transcribed, and analyzed using constructivist grounded theory. Quantitative and qualitative results were integrated and presented together. Results: From the retrospective cohort study, TGD individuals presenting for acute psychiatric care had increased measures of socioeconomic marginalization and were more likely to be diagnosed with a mood or personality disorder, and less likely a substance-related disorder. TGD individuals had increased 30-day post-ED follow-up (adjusted OR=1.21), but reduced 30-day follow-up post-hospitalization (aOR=0.81). The quantitative findings informed the qualitative study’s semi-structured interview guide and the purposive sampling strategy. A qualitative theory explaining the quantitative findings was co-constructed with the qualitative study participants. Participants described how chronic minority stress (developmental trauma, physical disability, neurodivergence, and marginalization) and inability to access care led to presenting to ED as one of few remaining doors to needed care. Autonomy, safety, and usefulness around the acute care experience influenced their decision post-discharge to 1) engage in care within the formal system, 2) prefer community care, or 3) avoid the system altogether. Participants offered explanations for each quantitative finding that are presented in joint displays with illustrative quotes and themes. Conclusions: TGD individuals who use acute mental healthcare have experienced greater marginalization and are more likely to follow up with mental healthcare after discharge from the ED but less likely to follow up after hospitalization, which is explained by transphobic experiences during hospitalization. Hospital staff and policies need to prioritize autonomy and address systemic transphobia to support access to care. Integrating TGD-specific community organizations into acute mental health services may help address the needs of TGD individuals more holistically.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".