Low utilization of skilled birth attendants in Ngorongoro Conservation Area, Tanzania: A complex reality requiring action
Bibliographic record
Abstract
Limited integration of contextual factors in maternal care contributes to slow progress towards achieving MDG5 in sub-Sahara Africa. In Ngorongoro, rural Tanzania, the maternal mortality ratio is high with 642 maternal deaths/100,000 live births. Skilled birth attendants (SBAs) assist only 7% of deliveries. This study, undertaken from 2009 to 2011, used Participatory Action Research involving local stakeholders (Maasai women and men, traditional birth attendants (TBAs), hospital staff) to examine reasons for low utilization of SBAs and moreover to develop proposals how to integrate contextual factors and local needs in the health care system. Interviews, observations and literature study were also conducted. Thaddeus and Maine’s Three Delays model is used to structure the analysis. Delaying factors in decision making at home: negative perceptions by the community on availability and quality of care in the hospital; discontinuity of care by TBAs; food and financial insecurity; desired nearness to cattle and family; limited recognition of maternal deaths; limited male health education and suboptimal birth preparedness. Delaying factors in reaching the hospital: vehicle and road limitations. Delaying factors in receiving hospital care: limited (human) resources and limited knowledge sharing at the hospital. Community members and health workers proposed: increasing food/financial security; tailoring male health education; combining TBA/SBA care to provide continuous, culturally appropriate labour support; creating separate maternity wards; increasing the number and training of staff; ensuring continuous availability of Emergency Obstetric Care. Applying solutions to increase hospital utilization seems complex as collaborative actions by multiple actors and institutions are needed to create both a needs based and clinically sound continuum of maternal care. To follow-up this process of integrating local solutions into the maternal care system, we suggest to adapt the WHO Strategic Approach—a top-down framework for the implementation of innovations—to fit this bottom-up approach.
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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".