“Many women use contraceptives in secret”: a qualitative study of health provider perspectives regarding barriers and enablers to reproductive health and antenatal care services in rural Tanzania
Bibliographic record
Abstract
Background Women in sub-Saharan Africa face numerous barriers to reproductive health and antenatal care (ANC) services. The objective of this study was to identify health provider perspectives regarding the barriers and enablers to reproductive health, ANC, and postnatal care (PNC) services in rural Tanzania. Methods A qualitative study was conducted in four districts of Tanzania and utilized key informant interviews (KIIs) and focus group discussions (FGDs). An interview guide was developed, focusing on individual and community-based factors (barriers and enablers) to accessing ANC and PNC services. Data were collected during December 2017 and May 2018 and analyzed using a thematic approach. Results Two major themes were identified as barriers to women accessing ANC and PNC services. First, factors related to women in the context of their family and community, for example (i) lack of autonomy in a patriarchal society, (ii) lack of knowledge and education regarding healthy pregnancy and pregnancy complications, (iii) lack of financial resources or control over financial resources, (iv) use of traditional birth attendants, (v) lack of male involvement, (vi) cultural beliefs as barriers to accessing family planning and ANC and PNC services. Second, factors present in the health system, for example (i) lack of infrastructure, equipment and health provider resources at health facilities, and (ii) lack of confidentiality and feelings of stigmatization when receiving health services. Reduced stigmatization against women with Human Immunodeficiency Virus (HIV) served as an enabler. Conclusions Overall, this study highlights the need to implement more initiatives in these rural districts to improve ANC and PNC services uptake. It also indicates the need to find strategies to improve male involvement and family support in the local context.
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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 | 0.010 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".