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Record W4391575166 · doi:10.1093/jsxmed/qdae001.192

(202) Baseline Reproductive and Sexual Health Knowledge Among Undergraduate Students in Manitoba, Canada

2024· article· en· W4391575166 on OpenAlexaffabout
Kunal Jain, Esha Jain, L. Wilson, Rubén Blachman-Braun, Premal Patel

Bibliographic record

VenueThe Journal of Sexual Medicine · 2024
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent Sexual and Reproductive Health
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsReproductive healthCurriculumDemographyLogistic regressionMedicineSocioeconomic statusFamily medicineInfertilityFamily planningDemographicsPregnancyPsychologyPopulationEnvironmental health

Abstract

fetched live from OpenAlex

Abstract Introduction Many undergraduate students are newly sexually active adults with unsafe sexual practices. While sexual education curriculums exist, their understanding of reproductive and sexual health is unknown. Objective We sought to assess undergraduate students' knowledge and attitudes on reproductive and sexual health. Our aim was to identify variables associated with knowledge deficiencies. Methods A novel, cross-sectional questionnaire was created with local expert input. The survey assessed respondents’ demographics, attitudes, and knowledge of contraception/family planning, sexually transmitted infections (STIs), and infertility. The survey was distributed online from January to March 2021 to undergraduate students at two universities in Manitoba, Canada, through their students’ unions. Local ethics board approval was obtained, participation was voluntary, and data was anonymized. After calculating median and interquartile ranges according to the data distribution, categorical variables were analyzed with Chi-squared tests and continuous variables were analyzed with Kruskal-Wallis tests. Univariable and multivariable-adjusted logistic regression analysis were used to assess variables associated with knowledge differences. A p-value < 0.05 was considered statistically significant. Results There were 309 respondents out of approximately 28,816 possible undergraduate students (n=309, response rate 1.1%). Of the respondents, 239 (77.3%) were females, 146 (47.2%) were ≥22 years old, 49 (15.9%) were from a high socioeconomic status (SES), and 264 (85.4%) were from Manitoba. Few felt that their post-secondary education on contraception/family planning (26.2%), STIs (34.6%), and infertility (4.5%) was adequate. Many felt at risk of having an unplanned pregnancy (45.3%) and contracting a STI (34.6%). The overall mean knowledge score was 65.5%, with averages of 71.7% correct for STIs, 65.6% for infertility, and 59.2% for contraception/family planning. There were significant differences in knowledge scores with age (p = 0.012), location of high school completion (p = 0.004), and university attended (p=0.044). On multivariate analysis, higher knowledge scores were associated with identifying as female (male OR = 0.39, 95% confidence interval (CI): 0.18-0.87; p = 0.021), older age (age 21 OR = 6.04, 95% CI: 1.78-20.49; p = 0.004 and ≥22 years OR = 4.07, 95% CI: 1.35-12.26; p = 0.012), and university attended (University of Manitoba OR = 1.97, 95% CI: 1.11 – 3.49; p = 0.021). On subgroup analysis, family SES was associated with higher STI knowledge scores (OR = 2.19, 95% CI: 1.07 – 4.48; p = 0.032). Conclusions Undergraduate students face unique barriers in obtaining adequate reproductive and sexual health knowledge. In particular, younger males who attend smaller universities, and possibly those who are from lower SES, may be at greater risk of negative outcomes. We highlight the need for improved access to education and supports to assist undergraduate students in making more informed decisions. Disclosure No.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.030
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.107
GPT teacher head0.436
Teacher spread0.329 · 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 source (direct Gemma or distilled Codex), 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".

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Citations0
Published2024
Admission routes2
Has abstractyes

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