Using experience to create evidence: a mixed methods process evaluation of the new free family planning policy in Burkina Faso
Bibliographic record
Abstract
BACKGROUND: In 2019, Burkina Faso was one of the first countries in Sub-Saharan Africa to introduce a free family planning (FP) policy. This process evaluation aims to identify obstacles and facilitators to its implementation, examine its coverage in the targeted population after six months, and investigate its influence on the perceived quality of FP services. METHODS: This process evaluation was conducted from November 2019 through March 2020 in the two regions of Burkina Faso where the new policy was introduced as a pilot. Mixed methods were used with a convergent design. Semi-directed interviews were conducted with the Ministry of Health (n = 3), healthcare workers (n = 10), and women aged 15-49 years (n = 10). Surveys were also administered to the female members of 696 households randomly selected from four health districts (n = 901). RESULTS: Implementation obstacles include insufficient communication, shortages of consumables and contraceptives, and delays in reimbursement from the government. The main facilitators were previous experience with free healthcare policies, good acceptability in the population, and support from local associations. Six months after its introduction, only 50% of the surveyed participants knew about the free FP policy. Higher education level, being sexually active or in a relationship, having recently seen a healthcare professional, and possession of a radio significantly increased the odds of knowing. Of the participants, 39% continued paying for FP services despite the new policy, mainly because of stock shortages forcing them to buy their contraceptive products elsewhere. Increased waiting time and shorter consultations were also reported. CONCLUSION: Six months after its introduction, the free FP policy still has gaps in its implementation, as women continue to spend money for FP services and have little knowledge of the policy, particularly in the Cascades region. While its use is reportedly increasing, addressing implementation issues could further improve women's access to contraception.
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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 | 0.310 | 0.226 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.004 | 0.010 |
| Research integrity | 0.003 | 0.003 |
| 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".