PER_2009-2011_WSP-IE_v01_M_v01_A_PUF
WSP Global Scaling up Handwashing Behavior Impact Evaluation, Baseline and Endline Surveys 2009-2011
Name | Country code |
---|---|
Peru | PER |
Other Household Health Survey [hh/hea]
The IE includes several rounds of household and community surveys: pre-intervention (baseline), concurrent (longitudinal), and post-intervention (endline). The surveys are designed to collect information on the characteristics of the eligible population and to track changes in desired outcomes.
In Peru, the handwashing project targets mothers/caregivers of children under five years old, and it is aimed at improving handwashing with soap practices. Children under five represent the age group most susceptible to diarrheal disease and acute respiratory infections, which are two major causes of childhood morbidity and mortality in less developed countries.
These infections, usually transferred from dirty hands to food or water sources, or by direct contact with the mouth, can be prevented if mothers/caregivers wash their hands with soap at critical times (such as before feeding a child, cooking, eating, and after using a toilet or changing a child’s diapers). In an effort to improve handwashing behavior, the intervention borrows from both commercial and social marketing fields. This entails the design of communications campaigns and messages likely to bring about the desired behavior changes, and delivering them strategically so that the target audiences are “surrounded” by handwashing promotion.
Some key elements of the intervention include:
• Key behavioral concepts or triggers for each target audience
• Persuasive arguments stating why and how a given concept or trigger will lead to behavior change, and
• Communication ideas to convey the concepts through many integrated activities and communication channels.
The objective of the IE is to assess the effects of the project on individual-level handwashing behavior and practices of caregivers and children. By introducing exogenous variation in handwashing promotion (through randomized exposure to the project), the IE also addresses important issues related to the effect of intended behavioral change on child health and development outcomes. In particular, it provides information on the extent to which improved handwashing behavior impacts infant health and welfare.
Sample survey data [ssd]
Version 1.0: The study includes information on the baseline, longitudunal and endline surveys.
2011-06-01
The survey covered the following topics:
Topic | Vocabulary |
---|---|
Impact Evaluation | World Bank |
Health | World Bank |
The sample included in the IE study is not representative of the Peruvian population at the national level because the selection of provinces and districts was random and not weighted by population, as would be necessary to be geographically representative. Because populations differ across provinces and districts, the three-stage sampling design introduced a type of bias (with respect to geographical representativeness) because selection probabilities varied across administrative units.
The household survey was based on cluster sampling, and included a total of 120 districts chosen among 80 provinces (both choices made at random). The expectation was to conduct a total of 3,500 household questionnaires and 120 community questionnaires (one per district). By the end of the survey, data was collected from 3,576 households and 120 districts in 80 provinces.
Name | Affiliation |
---|---|
Water and Sanitation Program | World Bank |
Name | Role |
---|---|
Kimetrica International | Data reduction endline |
Name | Role |
---|---|
Bill & Melinda Gates Foundation | Primary funding source for the impact evaluation |
The primary objective of the project is to improve the health and welfare of young children. The sample size (total number of households) was chosen to capture a minimum effect size of 20 percent on the key outcome indicator of diarrhea prevalence among children under two years old at the time of the baseline. The selection of households with children in this age group was made under the assumption that health outcome measurements for young children in this age range are most sensitive to changes in hygiene in the environment. Data was collected for household members of all age ranges and the corresponding data analysis was conducted for older children and adults as well. Power calculations indicated that, in order to capture a 20 percent reduction in diarrhea incidence, around 600 households per treatment arm would need to be surveyed. Therefore, since the evaluation consists of three treatment groups and two control groups, the final sample incorporates approximately 3,000 households, each with children less than two years of age at the time the survey was conducted. An additional 500 households were added to the sample size in order to address potential attrition (loss of participants during the project); thus the minimal necessary sample size was 3,500 households (around 700 households per arm).
To select the sample, the IE team used a three-stage sampling methodology:
• Stage 1: Province Level
From 195 total provinces in Peru, Pisco and Lima were excluded at the request of the implementation team.2 Of the remaining 193 provinces, 80 provinces were randomly chosen. Out of these 80 provinces, two groups of 40 provinces each were randomly formed: Group of Provinces 1 (GP1) and Group of Provinces 2 (GP2).
• Stage 2: District Level
In order to assess the impact of each of the components of the project in the health of children younger than five years old, the evaluation study has two main treatments, that is, one per component. These are the Mass Media Treatment at the provincial level, also referred to as Treatment 1 (T1), and the Social Mobilization Treatment at the district level, also referred to as Treatment 2 (T2). In order to evaluate and identify the health impacts of each component, a counterfactual to T1 and T2 is needed, which we refer to as the Control (C). The three groups, T1, T2, and C include households with children under two years old at the time of the baseline.
Out of the first group of 40 provinces, GP1, 40 districts between 1,500 and 100,000 habitants were randomly chosen to receive T1. From the second group, GP2, 80 districts between 1,500 and 100,000 habitants were selected randomly; 40 of them were randomly assigned to receive T2, and the other 40 districts to serve as C to T1 and T2.
• Stage 3: Household Level
For each of the three sets of 40 districts (120 districts total) allocated to T1, T2, and C, 15-20 households with children under two years of age were selected at random in each district. Also, in each of the 40 districts
Baseline 1 Completed interview -----> 3508 --->94.3
2 Incomplete interview ----->48 --->1.3
3 Not available ----->7 --->.2
4 Rescheduled interview ----->7 --->.2
5 Nobody at home ----->48 --->1.3
6 Temporarily away ----->59 --->1.6
7 Refused to participate ----->44 --->1.2
Total 3721
Endline 1 Completed interview ----->3526 --->99.4
2 Incomplete interview ----->3 --->.1
4 Rescheduled interview ----->7 --->.2
5 Nobody at home ----->7 --->.2
6 Temporarily away ----->4 --->.1
Total 3547
Baseline households in endline are: 3,486.
The following instruments were used to collect the data:
• Household questionnaire: The household questionnaire was conducted in all households and was designed to collect data on household membership, education, labor, income, assets, dwelling characteristics,water sources, drinking water, sanitation,observations of handwashing facilities and other dwelling characteristics, handwashing behavior, child discipline, maternal depression, handwashing determinants, exposure to health interventions, relationship between family and school, and mortality.
• Health questionnaire: The health questionnaire was conducted in all households and designed to collect data on children’s diarrhea prevalence, ALRI and other health symptoms, child development, child growth, and anemia.
• Community questionnaire: The community questionnaire was conducted in 120 districts to collect data on community/districts variables.
• Structured observations: Structured observations were conducted in a subsample of 160 households to collect data on direct observation of handwashing behavior.
• Water samples: Water samples were collected in a subsample of 160 households, to identify Escherichia coli (E. coli) presence in hand rinses (mother and children), sentinel toy, and drinking water.
• Stool samples: Stool samples were collected in a subsample of 160 households to identify prevalence of parasites in children’s feces.
Start | End | Cycle |
---|---|---|
2008-04 | 2008-08 | Baseline |
2011-02 | 2011-06 | Endline |
Field team members administered the instruments. Each field survey team consisted of a team supervisor, two health members, and three interviewers. Those teams working in districts where structured observations of handwashing behavior were collected included an extra person in charge of the observations. Thus, the field personnel for the collection of the baseline data included a total of 15 field supervisors, 30 health members, 45 interviewers, and 10 observers.
Field team supervisors were required to have previous fieldwork experience in conducting similar studies, a required level of superior technical education, and to show a satisfactory performance in all areas of training (anthropometry, biometrics, and especially questionnaire training). Health specialists had to be standardized in order to collect anthropometric, anemia, and Ages and Stages Questionnaire (ASQ) data. The Nutritional Research Institute (Instituto de Investigacion Nutricional), with support from the global IE team, conducted the training for the collection of childrelated data, and was in charge of the standardization in the three measures (anthropometrics, anemia tests, and ASQ). Interviewers were required to complete the training satisfactorily and conduct at least three interviews in under-the-average time. Finally, observers (for structured observations) had to complete the training course successfully and conduct three four-hour observations, of which the trainers supervised at least one. Specific training was designed for each member of the survey team according to the specifi c skills required for the task to be performed in the field.
Baseline: The baseline survey was processed using the assistance of Sistemas Integrales in Chile. A manual for the data entry system is attached under the title of: Data Entry Manual:Baseline.
Endline: Kimetrica International was contracted to design the data reduction system to be used during the endline. The data entry system was designed in CSPro (Version 4.1) using the DHS file management system as a standard for file management. Details of the system can be found in the attached manual entitled: Data Entry Manual for the Endline Survey.
The data entry system was based on a full double data entry (independent verification) of the various questionnaires. CSPro supports both dependent and independent verification (double keying) to ensure the accuracy of the data entry operation. Using independent verification, operators can key data into separate data files and use CSPro utilities to compare them and produce a report that indicates discrepancies in data entry.
The DHS system uses a fully integrated tracking system to follow the stages in the data entry process. This includes the checking in of questionnaires; the programming of logic in what is known as a system controlled environment. System controlled applications generally place more restrictions on the data entry operator. This is typically used for complex survey applications. The behavior of these applications at data entry time has the following characteristics:
Files were processed using the unique cluster number and then concatenated after a final stage of editing and output to both SPSS and STATA.
Furthermore, attempts were made to respect the values and the naming conventions as provided in the baseline. This required using non-conventional values for “missing” such as -99. In most cases the same value sets were applied or during the questionnaire review process the WSP was alerted to such discrepancies.
Not applicable
Although there was no formal or independent appraisal of the data, an appraisal was undertaken when the data files for: Peru, India and Vietnam were prepared for a WSP presentation in Mexico. These data were presented in a public forum and scrutinized by various analysts. There was a process of feeding back information which helped correct or format or revise the data.
Name | Affiliation | |
---|---|---|
Bertha Briceno | Water and Sanitation Program | bbriceno@worldbank.org |
Alex Orsola-Vida | Water and Sanitation Program | aorsolavidal@worldbank.org |
Access authority is defined in a policy document entitled: WSP Data Access Policy. This document is attached. However, the following is provided from the data access policy:
To access data, team members must complete a Data Access Request Form (attached). Although team members may already have physical access to a particular dataset, they are expected to complete a Data Access Request Form (attached) if they intend to conduct a new analysis and/or prepare a new abstract, conference presentation, or manuscript.
All Data Access Request Forms should be submitted to Bertha Briceno (bbriceno@worldbank.org). In the event that Bertha is unavailable, the data access request form should be submitted to Alex Orsola-Vidal (aorsolavidal@worldbank.org).
Once the data access request form is submitted and approved, Bertha or Alex will facilitate the team member's access to the necessary data. WSP will strive to centralize storage of the latest datasets for analysis by all team members. Until WSP centralizes data storage, the individual Country PIs will be able to distribute the latest datasets for their respective countries.
The responsible team member must ensure that data are not distributed to anyone other than researchers listed on the Data Access Request Form.
The following team members will have access to data upon request and approval of the Data Access Request Form (attached).
• Country PIs
• Global experts
• WSP team
• Students or trainees of country PIs, global experts, or WSP team members will have access to data only after the supervising PI, global expert, or WSP team member complies with the process described here, including submitting the student's signed request for data access and agreement to comply with authorship and publication guidelines described. It is the supervising team member's responsibility to ensure that the student comply with all guidelines contained within this document.
Use of the dataset must be acknowledged using a citation which would include:
World Bank Water and Sanitation Program. Peru WSP Global Scaling up Handwashing Behavior Impact Evaluation, Baseline and Endline Surveys 2009-2011. Ref. PER_2009_2011_WSP-IE_v01_M_v01_A_PUF. Dataset downloaded from [website/source] on [date]
WSP is a multi-donor partnership created in 1978 and administered by the World Bank to support poor people in obtaining affordable, safe, and sustainable access to water and sanitation services. WSP's donors include Australia, Austria, Canada, Denmark, Finland, France, the Bill & Melinda Gates Foundation, Ireland, Luxembourg, Netherlands, Norway, Sweden, Switzerland, United Kingdom, United States, and the World Bank. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the Water and Sanitation Program, the World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent.
(c) 2011
Name | Affiliation | |
---|---|---|
Claire Chase | Water and Sanitation Program (WSP) | cchase@worldbank.org |
Bertha Briceno | Water and Sanitation Program (WSP) | bbriceno@worldbank.org |
DDI_PER_2009-2011_WSP-IE_v01_M_v01_A_PUF
Name | Affiliation | Role |
---|---|---|
Kimetrica International | Compiled the DDI | |
Water and Sanitation Project | World Bank | Reviewed content of the DDI |
2011-08-07
Version 1.1: Adopted from "DDI-WSP-PER-IE2009-2011" DDI that was done by metadata producers mentioned in "Metadata Production" section.