Women at the receiving end: Exploring Couples’ experiences of infertility challenges in Nigeria
Bibliographic record
Abstract
Abstract Background Infertility remains a significant global health issue with profound emotional and social consequences, particularly in patriarchal societies. This study explores the lived experiences of infertile couples in Nigeria, focusing on societal perceptions, gendered blame, and the role of spirituality. Methods A qualitative exploratory design was adopted, with data collected from purposively sampled infertile couples attending the Federal Teaching Hospital, Ido-Ekiti, Nigeria. Semi-structured interviews were conducted, and thematic analysis was used to identify recurring patterns and themes. Results Thematic analysis identified two main themes and seven sub-themes. The first theme, Couples ’ Perception of Infertility, included five sub-themes: definition of infertility, perceived causes, perceived types, infertility as a feminine issue, and the role of spirituality. The second theme, Challenges of Couples Experiencing Infertility, comprised two sub-themes: women at the receiving end and poor societal support. Conclusion The findings shows the interplay of medical, cultural, and spiritual dimensions in shaping infertility perceptions. The study highlights the disproportionate burden on women and inadequate societal support, calling for public health interventions to address stigma and promote gender-inclusive reproductive health education.
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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 | 0.003 | 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 | 0.007 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".