Stigmatized by association: challenges for abortion service providers in Ghana
Bibliographic record
Abstract
BACKGROUND: Unsafe abortion is an issue of public health concern and contributes significantly to maternal morbidity and mortality globally. Abortion evokes religious, moral, ethical, socio-cultural and medical concerns which mean it is highly stigmatized and this poses a threat to both providers and researchers. This study sought to explore challenges to providing safe abortion services from the perspective of health providers in Ghana. METHODS: A descriptive qualitative study using in-depth interviews was conducted. The study was conducted in three (3) hospitals and five (5) health centres in the capital city in Ghana. Participants (n = 36) consisted of obstetrician/gynaecologists, nurse-midwives and pharmacists. RESULTS: Stigma affects provision of safe-abortion services in Ghana in a number of ways. The ambiguities in Ghanaian abortion law and lack of overt institutional support for practitioners increased reluctance to openly provide for fear of stigmatisation and legal threat. Negative provider attitudes that stigmatised women seeking abortion care were frequently driven by socio-cultural and religious norms that highly stigmatise abortion practice. Exposure to higher levels of education, including training overseas, seemed to result in more positive, less stigmatising views towards the need for safe abortion services. Nevertheless, physicians open to practicing abortion were still very concerned about stigma by association. CONCLUSIONS: Stigma constitutes an overarching impediment for abortion service provision. It affects health providers providing such services and even researchers who study the subject. Exposure to wider debate and education seem to influence attitudes and values clarification training may prove useful. Proper dissemination of existing guidelines and overt institutional support for provision of safe services also needs to be rolled out.
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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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| 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".