Evaluation of integrating family planning with maternal and child health services
Bibliographic record
Abstract
Family planning (FP) reduces the burden of unintended pregnancies and maternal and child mortality. Pakistan has the lowest modern Contraceptive Prevalence Rate (mCPR) in the South Asian region. Despite national efforts, poor access to FP services combined with community level barriers has left 17% of currently married women with an unmet need for FP and 46% of pregnancies are unintended, leading to high abortion rates. Recognizing the essential need for FP, this study’s aim was to design evidence informed intervention and evaluate the impact of integrating FP with Maternal, Newborn and Child Health (MNCH) service delivery model to increase Modern Contraceptive Methods (MCMs) coverage in rural Pakistan. A sequential exploratory mixed methods design was adopted comprising of qualitative and quantitative components. The qualitative component was to inform the intervention design based on healthcare workforce and community members’ perspectives. The quantitative quasiexperimental component of the study was undertaken to assess the effectiveness of FP with MNCH integration on MCMs uptake in two districts of rural Pakistan (Matiari and Badin). Interventions strategies were identified through a systemic review and meta-analysis. The intervention comprised healthcare workforce training, sustaining FP supplies, and community engagement; implemented through existing service delivery platforms at the healthcare facility and community levels. The interventions were delivered at six health care facilities in the intervention and similar level health facilities were selected in the control district. A comparative analysis of health facility data (using t-test) of Badin (control) and Matiari (intervention) showed a statistically significant difference across the MNCH continuum of care; whereby Badin had an average of 93.5 new FP clients and 18.8 follow-up visits compared to a mean of 281.7 new FP clients and 123.7 follow-up visits in Matiari. Baseline and follow-up surveys additionally conducted to measure population level impact also revealed a statistically significant increase of 11.3% in current use of MCMs in the intervention group (p-value <0.001) in the follow-up survey as compared to the baseline. This study shows that designing evidence-informed interventions to integrate FP with MNCH significantly improves MCM uptake and may have effective scale-up potential within similar settings.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".