Enhancing intersex healthcare: A qualitative study of parental perspectives on the role of genetics
Bibliographic record
Abstract
Intersex individuals, encompassing people with diverse sex characteristics that do not fit binary frameworks of sex, have long faced a history of medical secrecy, discrimination, and societal stigma, contributing to their limited social visibility. In recent years, increased awareness of intersex issues and a robust advocacy movement have drawn significant attention to the experiences of intersex individuals and their families. This study contributes to the existing literature by examining the experiences and needs of parents of intersex individuals within genetic healthcare systems, bridging a critical gap, and advocating for more comprehensive and supportive healthcare practices. Semi-structured interviews were conducted with 14 parents of intersex individuals, and reflexive thematic analysis was used to inductively generate four major themes. Themes highlighted the need for improved accessibility of intersex healthcare, the importance of multidisciplinary healthcare teams, and the significance of clinical diagnosis provided by genetics professionals. Furthermore, the study highlighted the necessity of a thoughtful approach to information provision and the impact of genetic investigations on family dynamics. Genetics professionals can play a pivotal role in raising awareness about intersex variations, improving diagnostic processes, collaborating within healthcare teams, and providing specialized support to address psychosocial concerns. The study underscores the importance of treating families as a collective entity and addressing the impact of genetic investigations on the family unit. By addressing the challenges and implementing the recommendations outlined, healthcare institutions can create a more compassionate, inclusive, and effective healthcare environment for the intersex community.
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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 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.009 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| 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".