Maternal health care decision-making process at the family level in Geita Region, Tanzania: A qualitative study
Bibliographic record
Abstract
Abstract Background : Most maternal deaths are preventable if a woman is able to identity danger signs and seek obstetric health care without delay. However, lack of knowledge on obstetric danger signs and a prolonged decision-making process at family level may contribute to the high maternal mortality. Currently, there is little known on how the process of decision-making at family level in seeking obstetric care is being made in Tanzania. Therefore, this study aimed to describe the process on decision-making at family level in seeking maternal health care during pregnancy, delivery and postpartum period in the Geita Region, Tanzania. Methods : A qualitative study using in-depth semi-structured interview was conducted at Chato District Hospital in the Geita Region with seven fathers and seven mothers who were attending the Reproductive Child Health Clinic.Participants were recruited using purposeful sampling and interviews were analyzed using content analysis. Results: Three themes emerged from this study, including recognition of danger signs, decision-making process, and perceived influencers for seeking maternal health care. Almost all participants were aware of obstetric danger signs, yet some gaps remained among husbands. The process of decision-making starts with the woman herself who then communicates to others for discussion but the final decision-making in seeking care is dominated by husbands, parents, or neighbors, rather than mothers alone. Observing danger signs and perceived quality of care available from the health facilities were the most predominate influencers for seeking maternal health care. Conclusion: While the process of decision-making in every family starts with the woman herself, others are consulted for discussion prior to reaching a decision about seeking maternal health care, resulting in delays in accessing care. It is positive that most of the decision makers had good understanding of obstetric danger signs and that observation of those danger signs encourage access of maternal health care. However, continued education on obstetric danger signs in the community is needed as well as quality care needs to be available and known to be provided at health care facilities to encourage early seeking of maternal health care. Keywords : maternal health; decision-making; Tanzania
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".