Knowledge, Attitude, and Practices of the General Population toward the Old-New Outbreak of Cholera in a Developing Country
Bibliographic record
Abstract
Background: In October 2022, the first case of cholera since 1993 was recorded in Lebanon. This study aimed to develop and validate a tool to explore the knowledge, attitudes, and practices (KAP) toward cholera infection and its prevention among the general population in Lebanon and identify the associated factors related to the KAP assessment to guide prevention and awareness strategies. The nation’s already precarious healthcare system might become overwhelmed by the response to the cholera outbreak. Therefore, evaluating the level of cholera-related KAP among the Lebanese population is crucial since it directly affects the disease’s treatment, control, and prevention. Methods: This online cross-sectional study was carried out between October and November 2022 during the cholera outbreak in Lebanon. Snowball sampling was used to recruit 448 adults living in Lebanon. Results: The suggested KAP scales had adequate structural and convergent validity and were internally consistent. The disease knowledge was inversely associated with the reluctance to receive educational information (β = −1.58) and cigarette smoking (β = −1.31) but positively associated with the female gender (β = 1.74) and awareness of vaccine availability and efficacy (β = 1.34). For attitude, healthcare professionals were less frightened than others (β = 2.69). Better practices were related to better knowledge (β = 0.43), while inadequate practices were associated with getting information from social media (β = −2.47). Conclusions: This study could identify notable gaps in the knowledge, attitudes, and practices, which varied according to participant characteristics. Cholera incidence can be reduced by improved community education and training, increased access to safe water, sanitation, and hygiene amenities, and changes in behavior. These findings warrant additional actions by public health stakeholders and governmental authorities to promote better practices and curb disease transmission.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".