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Record W4415380964 · doi:10.1080/15546128.2025.2574590

Beyond Contraception: The Need for Comprehensive Family Planning Education Among Undergraduate Students Interested in Health Professions

2025· article· en· W4415380964 on OpenAlexaff
Sara B. Oswalt, Suyapa Muñoz, Lisa N. Miura, Katelyn M. Sileo

Bibliographic record

VenueAmerican Journal of Sexuality Education · 2025
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Contraception
Canadian institutionsDiscovery Centre
FundersNational Institutes of Health
KeywordsFamily planningHealth professionsHealth professionalsPopulationHealth careProgram evaluationHealth educationQualitative research

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.305
Threshold uncertainty score0.626

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.044
GPT teacher head0.447
Teacher spread0.403 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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