Barriers to the effective treatment and prevention of malaria in Africa: A systematic review of qualitative studies
Bibliographic record
Abstract
BACKGROUND: In Africa, an estimated 300-500 million cases of malaria occur each year resulting in approximately 1 million deaths. More than 90% of these are in children under 5 years of age. To identify commonly held beliefs about malaria that might present barriers to its successful treatment and prevention, we conducted a systematic review of qualitative studies examining beliefs and practices concerning malaria in sub-Saharan African countries. METHODS: We searched Medline and Scopus (1966-2009) and identified 39 studies that employed qualitative methods (focus groups and interviews) to examine the knowledge, attitudes, and practices of people living in African countries where malaria is endemic. Data were extracted relating to study characteristics, and themes pertaining to barriers to malaria treatment and prevention. RESULTS: The majority of studies were conducted in rural areas, and focused mostly or entirely on children. Major barriers to prevention reported included a lack of understanding of the cause and transmission of malaria (29/39), the belief that malaria cannot be prevented (7/39), and the use of ineffective prevention measures (12/39). Thirty-seven of 39 articles identified barriers to malaria treatment, including concerns about the safety and efficacy of conventional medicines (15/39), logistical obstacles, and reliance on traditional remedies. Specific barriers to the treatment of childhood malaria identified included the belief that a child with convulsions could die if given an injection or taken to hospital (10/39). CONCLUSION: These findings suggest that large-scale malaria prevention and treatment programs must account for the social and cultural contexts in which they are deployed. Further quantitative research should be undertaken to more precisely measure the impact of the themes uncovered by this exploratory analysis.
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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 | 0.056 | 0.128 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.013 | 0.017 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".