An Evaluation of a Water, Sanitation, and Hygiene Program in Rural Communities Outside of Port-au-Prince, Haiti
Bibliographic record
Abstract
Background: In 2010, a massive earthquake left the capitol Port-au-Prince in ruins and destroyed infrastructure providing electricity, piped clean water, and waste removal to the region. Water, sanitation, and hygiene intervention programs attempt to reduce the burden of water-related disease in earthquake-affected regions. However, there are few evaluations of these programs, especially following natural disasters. Methods: Data provided by Samaritan’s Purse Canada’s WASH program were examined. The data set included a household (N=1198) and a latrine (N=167) survey that recorded household use of laundry pads, bath houses, hand-pumped drilled wells, health and hygiene education sessions, and latrines as well as demographic data. Data analysis was conducted in IBM SPSS Version 20.0. Descriptive statistics were computed, and statistical relationships were analyzed for 1.) Health and hygiene education session attendance and program outcomes and 2.) Household diarrheal disease and program interventions Results: This study found that households attending any of four health and hygiene sessions were significantly more likely to use program-provided bath houses and hand-pumped wells (p<0.05). Attendance was also significantly associated with increased knowledge of diarrheal disease prevention and hand washing technique. Households using the program-provided hand pump reported lower rates of diarrhea in children under five years old. Discussion: This study concluded that health and hygiene session attendance is positively associated with the utilization of program interventions. However, further improvements in data collection methodology are needed to fully understand the effects of this multi-intervention WASH program on target communities.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".