What mental health supports do people with intersex variations want, and when? Person-centred trauma-informed lifecycle care
Bibliographic record
Abstract
Several large-scale surveys around the world show the most frequently reported mental health diagnoses among people with intersex variations include depression, anxiety and PTSD. Wellbeing risks are also high, with individuals with intersex variations citing suicidal thoughts or attempts across their life-course – specifically on the basis of issues related to having congenital sex variations. The population mostly attributed their wellbeing risks to negative social responses from others, difficulties around having undergone interventions, or issues around gender/identity. In the Canadian context, there is a lack of formalised, charitable Canadian wide intersex networks, advocacy groups, universal mental health care approaches, or provincial signposting to services similar to those developed elsewhere. Using a life-cycle lens, a group of international researchers came together in this collaborative Canadian study to explore health care transitions that people with intersex variations might need or desire, at various stages of their life. A key finding from this ongoing study is that transition phases have the capacity to be especially difficult in the context of mental health, such that integrating person-centred and trauma-informed approaches into care with this population is both wanted and needed. This paper specifically takes a case study approach which analyses data from two participants who identified three major themes regarding mental health impacts: ‘worth, mastery, and adequacy’, ‘isolation and inferiority’, and ‘identity and integrity’. The fourth and final theme drew on integrated medicine to celebrate emerging ‘resilience and generativity’; a positive experience that had emancipatory benefits across the lifespan.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".