Determinants of Menâs Involvement in Sexual and Reproductive Health in Nigeria
Bibliographic record
Abstract
For too long men's role has been seen as marginal in the area of sexual and reproductive health (SRH).Despite the decision from the 1994 International Conference on Population and Development (ICPD), and the place of men in reproductive health (RH), the notion of many health-care providers that men are uninterested in taking responsibility for family planning and other RH issues still persists.This study explored factors that influence male involvement in reproductive health.Qualitative methodswere used to collect data using in-depth interviews and focus group discussions involving twelve in-depth interviews and ten focus group discussions.Six in-depth interviews each were conducted in Adamawa and Bauchi States respectively, comprising four for males and two for females.Five Focus group discussions each were also conducted in Adamawa and Bauchi States.Three of the FGDs in each state had all males and two had all females.The study found out that religion, pursuit of confidentiality, culture, contraceptive types, concentration of programming on women, and male egocentrism play a role in decreasing male involvement in RH services.Other factors which positively influence male participation in SRH health are: sports activities through using sporting activities to pass RH messages, home videos with RH messages, music which pass RH messages, attempts at reducing family size, fear of and awareness of STIs & HIV/AIDS, increased level of RH programmes which provide testing for STIs and HIV/AIDS, treatment and care together and awareness of reproductive health issues.The study concludes by recommending that there should be emphasis on men's participation in reproductive health since this could help draw attention to the need to do more for women as well.In other words, policies to increase men's participation may help improve women's programmes because more men would understand what SRH entailed and support better reproductive health care for women, as well as for themselves.
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".