Female college students' knowledge, attitude and practice towards sex and emergency contraceptives
Bibliographic record
Abstract
Background- At the local, regional, national and global levels, unsafe abortion takes a \ntremendous toll on girls, women, families, communities, health systems and nations. \nAn estimated 46 million induced abortions are performed annually with 78,000 deaths \nglobally each year. In Ethiopia, unsafe abortion accounts for nearly 60% of all \ngynaecological admissions and almost 30.0% of all obstetric admission, about 22-54% \nof direct obstetric deaths are due to unsafe abortion. EC is increasingly regarded as a \nmeans to reduce abortion rates \nObjective – The aim of this study is to assess the knowledge, attitude and practice of \nfemale college students’ towards sex and emergency contraceptives so as to prevent \nunintended pregnancy. \nMethods – A descriptive cross sectional survey was conducted among 352 sampled \nfemale college students of Dessie, Ethiopia from June 4 to June 5/2012. Selfadministered \nquestionnaire was used to collect the data. Data was entered into a \ncomputer using Microsoft Excel 2007 and analyzed using SPSS version 16.0 statistical \nsoftware and Binary logistic regression analyses are used to measure the associations. \nResult- The age of students ranged from 18 to 25 years. Of the total respondents \n36.6% ever had sexual experience, 53.3% know at least one regular modern \ncontraceptive method, 69.9% heard about emergency contraceptives (EC) but, only \n33.9 % had good knowledge about EC and 15.4% of them had ever used it. \nConclusion & recommendation- Less than fifty percent of the respondents were \nknowledgeable about EC. The correct knowledge of the method such as the time limit is \nlacking for most of the students. \nInformation, education & communication to increase awareness and knowledge about \nemergency contraceptive is important. Contraception information sessions should address; full details how the EC works and full details of how the contraceptives should \nbe taken
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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 | 0.005 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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".