Acute psychiatric care experiences and post-discharge trajectories among transgender and gender diverse adults: a constructivist grounded theory
Bibliographic record
Abstract
Background: Transgender and gender diverse (TGD) people experience disproportionately high rates of mental health challenges, often leading to increased use of acute psychiatric care (emergency departments and hospitalizations). However, little is known about their lived experiences during and after such care. Aim: To explore the lived experiences of TGD individuals in acute psychiatric care and examine how these experiences shape post-discharge trajectories. Method: Using constructivist grounded theory, we conducted a qualitative study with 15 TGD individuals in Toronto, Ontario, who had received acute mental healthcare. Participants were recruited from both clinical and community settings. Data were analyzed inductively to identify patterns in experiences and care pathways. Results: Cumulative minority stress, stemming from trauma, neurodivergence, physical health conditions, and social marginalization, contributed to mental health crises and influenced help-seeking. Participants' acute care experiences were shaped by autonomy, safety, and perceived usefulness, which informed three post-discharge pathways: engagement with formal mental health services, often facilitated by positive care experiences and access to dialectical behavior therapy; care through community organizations offering holistic, identity-affirming support; and avoidance of the mental health system following re-traumatization and loss of agency. Community-based care was seen as more effective than the biomedical model in addressing autonomy and social determinants of health. Conclusion: Acute mental healthcare systems must be reformed to better support TGD individuals by addressing systemic transphobia, integrating trauma-informed, intersectional approaches, and embedding community partnerships within formal care structures. Policies centering autonomy and validating lived experience may enhance engagement and improve outcomes during and after crises.
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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 | 0.014 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.017 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".