Beyond Contraception: The Need for Comprehensive Family Planning Education Among Undergraduate Students Interested in Health Professions
Bibliographic record
Abstract
Increased age is a primary factor of infertility, and women pursuing health careers may be especially affected due to required multi-year education and training. Few studies have examined undergraduate student voices about the intersection of pursuing a health career and family planning intentions. Filling that gap, this qualitative study conducted focus groups (N = 11) with cisgender female undergraduate students (N = 23) at a university located in southcentral Texas. A coding scheme established a priori was used to analyze results, with iterative development of the scheme as analyses occurred. Results indicated that participants had thought extensively about how their intended health career intersects with their desire for a family. Family, culture, gender, and the intersection of career aspirations and family desires were all influencing factors. Overall, students expressed concern about navigating the intersection of having a family and a health career, and their lack of knowledge about fertility and assisted reproductive technologies contributed to a lack of definitive planning for their lives. Students suggested strategies to address their lack of knowledge and increase their planning capabilities. These ideas can guide sexuality education intervention development and implementation to ensure that strategies consider potential issues across the lifespan and provide resources accordingly.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".