Women Mobile Lifeline Channel Is a Key Stimulant of MCH Services Use in Resource Constrained Settings: A Success Story of Women Health Channel Uganda
Bibliographic record
Abstract
Background Uganda has made progress in recent decades; however, the country still ranks among the top 10 countries in the world with high maternal, newborn, and child mortality rates. 336 women in every 100000 live births die due to preventable pregnancy related causes (under-five mortality rate 64/1000 live births; infant mortality rate 43/1000 live births; and neonatal mortality rate 27/1000 live births). Despite the growing global focus on reaching the last mile that necessitates the development of mHealth tools that best reach, empower, and mobilize the last mile women to seek and utilize critical and life-saving health care services as a vehicle for accelerating reduction of maternal and child deaths, mHealth tools in Uganda continue to limit focus on reporting and trucking of health indicators. Objective MIRA Channel is a single-window app with multiple channels on prenatal care, child immunization, newborn care, and family planning with the objective to improve maternal and child health outcomes in rural and resource-constrained settings. The app delivers information to women through interactive edutainment tools that builds on their knowledge, thus creating awareness on critical health issues and preempt timely use of MCH services. Methods Women Health Channel Uganda piloted the Women Mobile Lifeline Channel app in 15 public health facilities in Jinja district, Uganda, and particularly targeted pregnant women. A systematic review of records, particularly the health facility ANC register, was done to estimate the facility clientele size. Purposive random sampling was used to arrive at the survey sample. Two contact midwives and 5 VHTs were selected, trained, and given a connected mobile device at each of the implementing health facilities. Recruitment of women on the platform was done by VHTs using connected phones at community level, and 3489 pregnant women were studied for 16 months. Data was collected at baseline and at end line. Results Both at baseline and at end line, information on knowledge as well as usage of key MCH services was collected. All women had heard of ANC and the recommended place of delivery; however, only 59% at baseline had knowledge of the exact recommended number of ANC visits as opposed to 94% at end line. At baseline, 36% of women reported to have attended ANC 4 or more times at the most recent pregnancy as opposed to 82% at end line, while 63% of women at baseline reported to have given birth in a health facility for the previous pregnancy as opposed to 94% at end line. Sven neonatal deaths were reported in the cohort at baseline as opposed to 0 maternal deaths and 1 neonatal death at end line. Conclusions The pilot showed that one critical determinant of use of MCH services is the overall client knowledge and the perceived available support mechanism in the face of challenges. mHealth tools ought to expand focus to include stimulation of two-way mobile-based interactions that reinforce behavior change and preempt use as such. The Women Mobile Lifeline Channel that Women Health Channel is implementing offers lenses for Uganda and other countries to walk towards meaningful ICT integration in health.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".