ASSISTED REPRODUCTIVE TECHNOLOGIES (ART) EQUITY, JUSTICE AND AUTONOMY IN GHANA
Bibliographic record
Abstract
ABSTRACT Restrictive legislation, which is the main barrier to some assisted reproductive technology (ART) services in many countries, is non-existent in Ghana. However, ART services are concentrated in the capital cities of only four out of the sixteen regions, serving predominantly middle- and upper-class individuals. There is limited evidence about the factors preventing broader access to ART services in Ghana, and this study aims to document these barriers. A cross-sectional survey was conducted in July 2024 across all 22 fertility centers in Ghana, using two structured questionnaires administered via Google App to 61 ART personnel and 104 treatment defaulters. Results showed that mentorship from senior colleagues (65.57%) was the most common way for ART professionals to acquire skills. Almost all (91.80%) professionals offered a full range of ART procedures, but 86.89% advocated for regulated practice. They identified high treatment costs (70.49%) and lack of awareness (16.39%) as the most significant barriers. Among treatment defaulters, 88.47% had sought ART services based on word-of-mouth recommendations, compared to only 4.8% influenced by traditional or social media. More than half (50.96%) of the women were in their thirties, and 48.08% required in vitro fertilization (IVF). While 58.65% sought treatment within five years of infertility, 70.2% discontinued due to high costs, and 35.57% due to partner non-availability. Despite the absence of restrictive policies for ART services in Ghana, Prohibitive costs, partner non-availability, and lack of awareness limit access. However, ART professionals expressed the need for regulated practices.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".