Use of any contraceptive method among women in rural communities in the eastern region of Ghana: a cross-sectional study
Bibliographic record
Abstract
BACKGROUND: In Ghana, there is an increase in contraceptive use for traditional and modern methods in rural areas. This study seeks to examine the prevalence and determinants of current use of any contraceptive method among women of reproductive age in the rural Eastern Region of Ghana. METHODS: A community-based cross-sectional study was conducted among women of reproductive age in the rural Eastern region of Ghana. A structured questionnaire was used to interview women in rural Lower Manya and Upper Manya Krobo districts of Eastern region who were selected using a simple random sampling technique. The data were analysed using Stata version 16. A Binary logistic regression was used to examine the determinants of current use of any contraceptive use (traditional and modern methods). RESULTS: The prevalence of contraceptive use was 27.8%. In the adjusted analysis of binary logistic regression, contraceptive use was significantly lower (aOR = 0.24; 95%CI = 0.10-0.56; p = 0.001) among respondents aged 41-49 years compared to those aged 18-35 years. Contraceptive use was significantly lower among migrants (aOR:0.53; 95%CI:0.28-0.99; p = 0.048) compared with non-migrant. CONCLUSION: The prevalence of any contraceptive use among rural women was low. Government and other stakeholders need to create awareness about contraception in the rural areas of Eastern region of Ghana and that would help increase contraceptive methods utilization. In addition, family planning programs should target migrants to design an intervention to increase contraceptive use in rural areas.
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 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 | 0.001 |
| 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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".