Factors hindering health care delivery in nomadic communities: a cross-sectional study in Timbuktu, Mali
Bibliographic record
Abstract
BACKGROUND: In Mali, nomadic populations are spread over one third of the territory. Their lifestyle, characterized by constant mobility, excludes them from, or at best places them at the edge of, health delivery services. This study aimed to describe nomadic populations' characteristics, determine their perception on the current health services, and identify issues associated with community-based health interventions. METHODS: To develop a better health policy and strategic approaches adapted to nomadic populations, we conducted a cross-sectional study in the region of Timbuktu to describe the difficulties in accessing health services. The study consisted in administering questionnaires to community members in the communes of Ber and Gossi, in the Timbuktu region, to understand their perceptions of health services delivery in their settings. RESULTS: We interviewed 520 individuals, all members of the nomadic communities of the two study communes. Their median age was 38 years old with extremes ranging from 18 to 86 years old. Their main activities were livestock breeding (27%), housekeeping (26.4%), local trading (11%), farming (6%) and artisans (5.5%). The average distance to the local health center was 40.94 km and 23.19 km respectively in Gossi and Ber. In terms of barriers to access to health care, participants complained mainly about the transportation options (79.4%), the quality of provided services (39.2%) and the high cost of available health services (35.7%). Additionally, more than a quarter of our participants stated that they would not allow themselves to be examined by a health care worker of the opposite gender. CONCLUSION: This study shows that nomadic populations do not have access to community-based health interventions. A number of factors were revealed to be important barriers per these communities' perception including the quality of services, poverty, lifestyle, gender and current health policy strategies in the region. To be successful, future interventions should take these factors into account by adapting policies and methods.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".