Health Workers’ Attitudes Toward Adverse Gender Norms and Implications for Young People’s Sexual and Reproductive Health in Nigeria
Bibliographic record
Abstract
Background. Adverse gender norms within the health care system are detrimental to the sexual and reproductive health of young people. This study assessed the attitudes of health workers toward adverse gender norms related to intimate partner relationships across three domains: intimate partner violence (IPV); sexuality; and reproductive health behavior. Methods. A cross-sectional quantitative survey was conducted among 255 health workers in youth-friendly primary health centers in Ebonyi State, Nigeria. Attitudes to gender norm statements were assessed on a 3-point scale of agree (3 points), partially agree (2 points), and disagree (1 point). Mean attitude scores were estimated for each statement and the predictors of attitudes were determined through multiple linear regression analysis with p-value set at .05. Results. Majority of the health workers held gender biases regarding male control over sexual decision-making, men’s higher desire and value for sex, and the woman’s responsibility to prevent pregnancy. Over 40% of the respondents associated women carrying condoms with promiscuity, and 39.6% believed that only men have the “social” rights to purchase condoms. Urban residence predicted health workers’ attitudes to adverse gender norms related to sexuality (β = −.179, p = .003). Conclusions. Findings from this study provide a basis for in-service training programs that are designed to change the attitudes of health workers to adverse gender norms and transform their practices.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".