Evaluation of Knowledge, Attitude and Performance of the Mothers of Children Affected by Cutaneous Leishmaniasis
Bibliographic record
Abstract
Background Cutaneous leishmaniasis (CL) is one of the health problems of many tropical and subtropical regions and is endemic in many parts of Iran especially. Cutaneous leishmaniasis not only is a health problem but also is a social and cultural problem in Iran. Education about health for high risk population seems to have a critical role in prevention of leishmaniasis and therefore evaluation of knowledge, attitude and performance are of importance. For the success of prevention and control programs of any disease, the most important prerequisite is community participation. Program implementers need to understand the disease-related knowledge, attitude, and practices (KAP) of the community, because these are the important determinants of community participation. There are no data from Iran focusing on these aspects, and thus this study presents the information on KAP related to cutaneous leishmaniasis (C.L) in Iran. Methods In this study 166 mothers that had at least one child with CL were studied. Data collection was performed using questionnaires that were designed by epidemiologist and were analyzed using SPSS software. Results The mean of KAP score was 15.7 ± 1.6 (range of 11.5–19). 48 mothers (28.9%) had weak KAP, 79 mothers (47.6%) had average KAP and 39 mothers (23.5%) had excellent KAP. Conclusion According to our results, about 28.9% the mothers had inappropriate KAP score about leishmaniasis highlighting the fact that at least one third of the Isfahan population needs practical education about combating with leishamaniasis. To close the gap between the knowledge and practice of the mothers, face to face education and use of instructional aides are recommended.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".