Reproductive health experiences of women and non-binary people with early psychosis: a qualitative study
Bibliographic record
Abstract
BACKGROUND AND HYPOTHESIS: Psychosis typically emerges in young adulthood and can impact reproductive health, including risk for suboptimal fertility and unplanned pregnancies. This study aimed to explore the reproductive health experiences of young women and non-binary people with psychosis. STUDY DESIGN: In this qualitative study, young women and non-binary service users with experience of early psychosis in Toronto, Canada participated in semi-structured interviews about their reproductive health experiences (sexual health experiences analyzed separately). Clinicians providing healthcare for this population also participated in interviews/focus groups. Thematic analysis was used to describe core themes among service users, then understand how clinician perspectives related to these. STUDY RESULTS: Interviews with service users (n = 19, aged 18-31; cisgender women n = 15, transgender women n = 2, non-binary individuals n = 2) yielded two core themes: (1) Complex reproductive health needs exist irrespective of psychosis, and (2) Psychosis does specifically impact reproductive health priorities and plans. These were discussed across three clinical content areas: contraception, menstruation, and future pregnancy/family planning. A final theme emerged from clinicians (n = 36): (3) Clinicians grapple with clinical complexity, and sometimes have different priorities than their patients (e.g., menstruation was a priority for service users only). CONCLUSIONS: This study offers insights into the reproductive health experiences of women and non-binary individuals with early psychosis, including complexity that exists irrespective of psychosis, and additional psychosis-related complexity. The study also explored clinicians' perspectives, and identified areas of discordance between service user and clinician perspectives (e.g., related to menstruation). Findings can help shape interventions to improve this population's reproductive health.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".