Reproductive health and pregnancy experiences of women with spina bifida: A qualitative study
Bibliographic record
Abstract
PURPOSE: Despite an increasing number of individuals with spina bifida reaching reproductive age, there has been a paucity of research into their reproductive health care needs. The objective of this study was to better understand the reproductive health experiences of self-identified women with spina bifida using qualitative methodology. METHODS: A phenomenological study design was used to address this objective. Women with spina bifida identified their interest in participating in a semi-structured interview after completing an online reproductive health survey. Interviews were recorded and transcribed verbatim. Qualitative analysis followed a phenomenological approach using Dedoose software. RESULTS: Twelve self-identified women with spina bifida participated. They described experiences in four domains: sexual education, pregnancy, labor and delivery, and postpartum. In addition, an intersecting domain of social justice and advocacy emerged. Numerous themes are described, including a lack of tailored sexual health information, impact of pregnancy on function, attitudes towards delivery method, and parenting challenges. CONCLUSION: This study explored the continuum of reproductive health experiences of women with spina bifida. They face unique reproductive health challenges that provide an opportunity for health care providers to offer more holistic care.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.004 |
| 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".