Premarital sexual practice and its predictors among university students: institution based cross sectional study
Bibliographic record
Abstract
INTRODUCTION: Adolescents are susceptible to different social, peer and cultural pressures that Drives them into earlier sexual experimentation. Despite the fact that delaying sexual activity until marriage reduces the spread of HIV/AIDS and various sexually transmitted infections (STI), sexual activities among youths have been reported to be increasing worldwide. METHODS: Institution Based cross-sectional survey was conducted between January 2016 to March 2016. A total of 604 students were included in the study using multi-stage sampling technique. Mixed Quantitative and Qualitative approach was applied. Bivariate and multivariate logistic regression model was fitted to identify factors associated with premarital sexual practice. RESULTS: The proportion of premarital sexual practice in the study area was found to be 54.3%. The mean age of first sexual debut was 18.7±1.96. Half (50.6%) of these sexual activities were performed because of student's interest to meet their sexual desire. Being Male, watching pornography and High academic performance were the factors significantly associated with premarital sexual practice. CONCLUSION: The study had revealed that more than half of the participants were sexually active. Being male, watching pornography and high academic performance were predictors of premarital sexual practice. Therefore, Institute of Medicine and health science, gender office and HIV resource center have to organize different programs targeting at bringing behavioral change to minimize the prevailing prevalence of premarital sexual practice as well as its common consequences.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".