Can she make it? Transportation barriers to accessing maternal and child health care services in rural Ghana
Bibliographic record
Abstract
BACKGROUND: The Ghana Community based Health Planning and Services (CHPS) strategy targets to bring health services to the doorsteps of clients in a manner that improves maternal and child health outcomes. In this strategy, referral is an important component but it is threatened in a rural context where transportation service is a problem. Few studies have examined perceptions of rural dwellers on transportation challenges in accessing maternal health care services within CHPS. METHODS: Using the political ecology of health framework, this paper investigates transportation barriers in health access in a rural context based on perceived cause, coping mechanisms and strategies for a sustainable transportation system. Eight (8) focus group discussions involving males (n = 40) and females (n = 45) in rural communities in a CHPS zone in the Upper West Region of Ghana were conducted between September and December 2013. RESULTS: Lack of vehicular transport is suppressing the potential positive impact of CHPS on maternal and child health. Consistent neglect of road infrastructural development and endemic poverty in the study area makes provision of alternative transport services for health care difficult. As a result, pregnant women use risky methods such as bicycle/tricycle/motorbikes to access obstetric health care services, and some turn to traditional medicines and traditional birth attendants for maternal health care services. CONCLUSION: These findings underscore the need for policy to address rural transport problems in order to improve maternal health. Community based transport strategy with CHPS is proposed to improve adherence to referral and access to emergency obstetric services.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".