Comparative status of safe water use and hygiene practices in areas with and without NGO-Ied Water, Sanitation and Hygiene (WASH) Programme
Bibliographic record
Abstract
More than 90% people in Bangladesh have access to improved water supply system, \nbut arsenic is posing a threat to this achievement. Additionally, hygiene is considered \nas one of the challenging areas to deal in the development sector. A number of \norganizations (both government and non-goverment) are working to improve the water \nsupply, sanitation and hygiene practices through various water, sanitation and hygiene \nprogrammes. \nOBJECTIVE \nThe overall objective of this study is to reveal the role of non-government \norganizations (NGOs) in improving safe water use and hygiene practices by the rural \npeople of Bangladesh. \nMETHODS \nTen upazi/as with both NGO-Ied sanitation programme intervention and without any \nsuch activity (Comparison group) were selected for the study. Among the study \nupazilas, four were comparison upazilas, three were with BRAC facilitated WASH \nprogramme intervention areas and the rest three were with other NGO-Ied intervention \nareas. A multistage 30-cluster sampling method was adopted and 420 households \nwere selected randomly from every upazila for the survey. In selecting 30 villages from \nevery upazila, interval-sampling method was used. \nKEY FINDINGS \n1. Tubewell water was used predominantly for drinking in the study areas. \nSignificantly higher proportion of households in the BRAC WASH areas used \ntubewell water for drinking than the comparison and other NGO intervention \nareas (p<0.001). \n2. The expenditure for tubewell drilling was mostly covered by self arrangement \n(95.1 %) in the study areas. However, in BRAC WASH intervention areas 1.2% \nand in other NGO-covered areas 1.1 % tubewells were financed by NGOs. \nHouseholds not having their own tubewell mentioned financial problem (90.8%) \nas the major reason for not being able to install tubewell. \n3. Overall knowledge about the demerits of using arsenic-contaminated water in the \ncomparison areas was found less than the NGO-Ied WASH intervention areas. \nRegardless of the NGO-facilitated WASH programme prevalence, social \ninstitutions (54%), NGOs (23.5%) and mass media (26.6%) were the most \ncommon sources of information for knowing the demerits of using arseniccontaminated \nwater. \n4. Significantly higher proportion of people in NGO intervention areas (either BRAe \nor other NGOs) mentioned to wash hands during critical times than the \ncomparison areas. The overall hygiene practice among the households in the \nother NGO intervention areas with regard to all relevant issues was found higher \nthan the BRAe WASH and comparison areas, since less proportion of \nrespondents mentioned not to know about the hygiene issues (p
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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 | 0.002 |
| Science and technology studies | 0.000 | 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) | 0.003 | 0.001 |
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".