Determination of different social groups’ level of knowledge about malaria in a multicultural Amazonian cross-border context
Bibliographic record
Abstract
Abstract Background A steady decline in the number of cases of malaria was observed in the 2000s in French Guiana. This enabled regional health policies to shift their public health goal from control to elimination. To include inhabitants in this strategy, the main objective of this study was to describe knowledge about malaria, and related attitudes and practices in persons living in the French Guiana border. Methods We conducted a survey in people over 15 years old living in the twelve neighbourhoods of Saint-Georges de l’Oyapock with the highest malaria incidence. It comprised a 147-item questionnaire which collected data on socio-demographic characteristics and included a Knowledge Attitude and Practices survey on malaria. Knowledge-related data were studied using exploratory statistical methods to derive summary variables. A binary variable assessing level of knowledge was proposed and then assessed using exploratory approaches. Results The mean age of the 844 participants was 37.2 years [15.8], the male/female sex ratio was 0.8. In terms of nationality, 485 (57.5%) participants were Brazilian and 352 (41.7%) French. One third (305, 36.1%) spoke Brazilian Portuguese as their native language, 295 (34.9%) the Amerindian language Palikur, 36 (4.3%) French. The symptoms of malaria and prevention means were poorly known by 213 (25.2%) and 378 (44.8%) respondents, respectively. A quarter (206, 24.4%) did not know that malaria can be fatal. Overall, 251 people (29.7%) had an overall poor level of knowledge about malaria. Being under 25 years old, living in a native Amerindian neighbourhood, having an Amerindian mother tongue language, having risk behaviours related to gold mining were significantly associated with a poor level of knowledge. Conclusions This study is the first to describe the poor level of knowledge about malaria in populations living in the malaria endemic border area along the Oyapock river in French Guiana. Results will allow to reinforce, to diversify and to culturally adapt prevention messages and health promotion to increase their effectiveness with a view to quickly reaching the goal of malaria elimination through empowerment.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".