Knowledge, Attitude and Practice of Temporary Artificial Methods of Contraception Among Women of Child Bearing Age in Awka South Local Government Area
Bibliographic record
Abstract
BACKGROUND: Contraception is the procedure of preventing pregnancy when it is not desired (MedicineNet, 2018). It is broadly divided into natural and artificial methods of which the artificial is further subdivided into Temporary and Permanent methods. METHODS: This research exercise was conducted in Awka South Local Government Area in Anambra State, Nigeria consisting of Nine Towns namely Amawbia, Awka, Ezinato, Isiagu, Mbaukwu, Nibo, Nise, Okpuno and Umuawulu (Wikipedia, 2018). Questionnaires were administered by an interviewer which consists of 5 sections while data was analyzed using SPSS (Statistical Package for Social Sciences) and the results were chi-squared at appropriate times and data were presented in forms like prose, tables, and charts. RESULTS: 78.9% of the respondents were aware of temporary artificial methods of contraception; 44.3% of correspondents with knowledge of temporary artificial contraceptives got their information from friends while 22.4% of the correspondents got theirs from school which reflects a low level of sex education in our homes and religious institutions. Only 18.4% could actually identify intra-uterine contraceptive devices from a list of options While 43.2% could actually identify a contraceptive pill within a list of options. The study also showed that the oral contraceptive pill most known to 50.4% of the correspondents is postinor-2 while the intra-uterine device most commonly known to those with knowledge of intra-uterine contraceptive device was Mirena which is about 65.8% of the correspondents. Also, this research revealed that 49.2% admitted to having used temporary artificial contraceptives. CONCLUSION: Despite the high level of awareness of temporary artificial contraceptives methods, its level of practice is quite low in this part of the country and the major factors influencing the knowledge and attitude of the participants towards temporary artificial contraceptives are marital status and educational level.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".