Building Parental Capacity to Help Child Development: A Randomized Controlled Trial of the Save the Children Early Childhood Stimulation Program in Bangladesh 2013-2014, Baseline Survey
Other Household Survey [hh/oth]
Save the Children has developed a low-cost and potentially scalable early stimulation program that delivers actionable messages to mothers and other caregivers that show them how to interact and play with young children. American Institutes for Research (AIR) and its research partners at Data International, the International Centre for Diarrhoeal Disease Research, Bangladesh, and Minhaj Mahmud, the head of research of BRAC Institute of Governance of BRAC University, are conducting a cluster-randomized control trial to evaluate the impact of the early stimulation program in the regions of Satkania, Muladi, and Kulaura in Bangladesh. The study is also receiving advice from a Technical Advisory Board consisting of child development and nutrition specialists and government officials in Bangladesh.
In this evaluation, community clinics within the same union are randomly assigned to either receive the Save the Children intervention or not. Data on individual child outcomes and family stimulation behavior are collected from households within the catchment areas of these community clinics. Data from service providers operating within each community clinic’s catchment area are also collected.
Seventy eight community clinics are participating in the study, with half receiving the intervention (the treatment group) and half not receiving it (the control group). Thirty three households with children between 3 and 18 months of age residing in the catchment area of each community clinic at the time of baseline data collection were randomly sampled, resulting in a total sample size of 2,574 households, half treatment and half control.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
The unit of analysis consists of households with children between 3 and 18 months of age residing in the catchment area of participating community clinics at the time of baseline data collection.
- v02 (August 2015)
The impact evaluation team at American Institutes for Research (AIR) discovered a typo in the treatment status variable for the files that were uploaded on September 8, 2014 in the Microdata Library. The new data files correct for this typo by modifying the treatment status variable. Please note that only the datasets that include the treatment status variable have been modified. These files are: SIEF_Bayley_baseline_Aug2015.dta, SIEF_HouseholdSurvey_baseline_Aug2015.dta and SIEF_ServiceProviderSurvey_baseline_Aug2015.dta.
v02 datasets replaced v01.
- v01 (September 2014)
The intervention is delivered through community clinics by service providers. Community clinics were randomly assigned to the treatment condition and represent the cluster-level unit of observation. Households residing in the community clinic catchment area with children aged between 3 and 18 months were randomly selected and targeted during the baseline data collection period. Household survey and direct child measures were collected from both the household and the children themselves.
AIR, ICDDR,B, and DI worked with Save the Children, the World Bank, and the advisory board to develop the study instruments. The team developed the baseline data collection instruments, drawing from existing national and international surveys. The core indicators include child development outcomes, anthropometric measures, and parenting stimulation questions, although the final instruments contain many additional relevant indicators. Where possible, indicators were measured using questions and approaches that have already been field tested in Bangladesh to ensure that they were appropriate for the local context and the target populations. Baseline data were collected from eligible households, health assistants, family welfare assistants, and community health care providers operating in the selected community clinics, and district-level health personnel. The questionnaires are described in the Questionnaires section and copies are attached as external resources.
Bangladesh is divided into seven major administrative regions called divisions, and the study takes place in three of Bangladesh’s seven divisions: Barisal (a southern district), Chittagong (a district in the southeast), and Sylhet (a district in the northeast). Within these three divisions, the study is located in three districts: Barisal (in the division of Barisal), Chittagong (in the division of Chittagong) and Moulvibazar (in the division of Sylhet). Districts are subdivided into subdistricts, or upazilas. Within these three districts, the study is located in three upazilas: Muladi (in the district of Barisal), Satkania (in the district of Chittagong), and Kalaura (in the district of Moulvibazar). Upazilas are subdivided into unions, and the study takes place in 30 unions: 4 unions in Muladi, 16 unions in Satkania, and 10 unions in Kalaura.
The full universe of the evaluation consists of households with children between 3 and 18 months of age residing in the catchment area of the 78 community clinics at the time of baseline data collection.
Producers and sponsors
American Institutes for Research
American Institutes for Research
World Bank Strategic Impact Evaluation Fund
The study sample frame was generated from community clinic health assistant records, which have the advantage of being the centralized government document of record containing the population frame for all households with children under five years of age. The health assistant dataset included data for all three upazilas of interest. Based on an examination of the extant health assistant dataset described above, the study excluded 11 unions (out of a total of 41 unions) located in these three upazilas. Six of the unions were removed because data were not available. A further five unions were removed because they only had one community clinic (the study design requires each union to have at least one community clinic for each of the two treatment conditions). The final sampling frame included 78 community clinics located in 30 unions.
The sample frame was generated within each community clinic, and the units in the frame are households with children aged between 3 months and 18 months of age, which were situated in the selected community clinics' catchment areas during the period of the baseline data collection. The rationale for restricting the frame to households with children aged three months or older was that the main developmental assessment tool chosen for the evaluation-the BSID-III-has not been previously validated on children under the age of three months in Bangladesh. Early child development specialists consider the BSID-III test to be the gold standard assessment of development for children under 42 months of age, and it has been adapted by the team for use in Bangladesh. Because the BSID-III test is only valid for children under 42 months of age, we had to restrict the upper age limit of participating children to 18 months or younger at the time of baseline data collection in order to collect valid endline data 24 months later. To be eligible, the household had to reside in the catchment area during the baseline data collection period (November 2013-January 2014).
Initial Sampling: Using the health assistant records, the team created a list of households with at least one child aged between 3 and 18 months during the baseline data collection period. The team used a reference date of October 21, 2013, to calculate the age (in months) of the target children, and the team will collect endline data by October 2015, when the children will still be under 42 months of age.
Finally, within each community clinic catchment area, we randomly selected 33 households with children aged between 3 months and 18 months (as of October 21, 2013). The same set of households surveyed during the baseline data collection period will be surveyed during the endline data collection period.
Replacement Sampling: Anticipating that some households would be ineligible or would refuse to participate in the study, the team developed rules for replacing ineligible or "out-of scope households" and refusal households, following the guidance of two survey methodologists from AIR. Twenty additional replacement households were randomly selected from within each community clinic and included in a separate list, with each household randomly sorted from 1 to 20. When any of the originally selected 33 households were found to be ineligible or refused to participate, the field interviewer replaced it with the first household from the 20-household replacement list. Field interviewers continued replacing households in order. A careful differentiation was made between ineligible and refusal households.
Ineligible or "out-of scope" households: This category includes households that were randomly selected to be part of the sample but did not fit the target sample description of "Households with children from 3-18 months of age that live in the selected community clinics' catchment areas during the period of the baseline data collection." Out-of-scope households included the following cases:
a) Households that had permanently left the catchment area. These 300 households had resided in the catchment area during birth record data collection, but by the time of the baseline data collection they had relocated to a different residence outside the catchment area. In these cases, more than one source (such as neighbors or health assistants) confirmed that the household had moved.
b) Households with incorrect location information in birth records. In 291 cases, the selected households were not able to be located. This class of out-of-scope households includes two groups. The first group consists of the households who did not permanently reside in the catchment area of the selected community clinic, but had been registered in the health assistant record because they received services while they were visiting relatives or otherwise transiting through the community clinic's catchment area. The second group consists of households whose birth records were fabricated. This was confirmed to be the case in two community clinics, where a large number of households could not be located. (In response to this finding, the field data team met with the relevant HA, as well as representatives from Save the Children).
c) Households with children ineligible due to inaccurate date of birth. In 173 households, the birth records had an inaccurate date of birth for the child, and the child was not in the age range of 3-18 months old.
d) Households with temporarily absent families. In 159 cases, the households were located but the respondents were not available for interview because they were not in the village and were temporarily staying elsewhere (often visiting relatives).
Refusals: This category includes both households that refused to participate in the study and households that began but did not complete data collection. Thirty-nine eligible households (1.5% of the sample) did not agree to fully participate in the study. In 12 cases, the household refused to participate in any capacity. In 27 cases, the households began the household survey but later decided not to complete data collection (i.e., they did not participate in the BSID-III test or the anthropometric measures). For all 39 cases of refusal, the data collectors completed a non-complier questionnaire that captured some basic characteristics of this group to compare with the compliers.
Field Sampling: In cases where the field team was unable to complete data collection with a full set of 33 households in a community, even after exhausting the 53 randomly selected households (33 households from the original sample and 20 replacement households), the study employed an additional field replacement process. A total of 454 households from among the 2,574 were sampled using this method. The field replacement process was necessary because a new random selection from the birth record was impractical; either the birth record data were inaccurate or households had relocated. In order to locate replacements, the field team visited a household neighboring the missing household. If there was an eligible child in that household and that child also appeared in the master list that was collected from the health assistant, we selected that household. If this was not the case, we asked to be referred to the nearest households (within the area of the missing house) with infant children, and we repeated the process. These households were then cross-checked with the list of 53 households to avoid duplicative data collection, and the field team visited the nearest household with an infant child that most closely matched (in terms of the age range and the gender of the missing child) the random selection and neighbors' information. If the original neighbor's household contained an eligible child, the interview was performed there. If the field team was unsuccessful in locating the nearest eligible household, the process was repeated by asking neighbors of the next missing household in the sample. As noted, this process began only after the original list of 53 households in a community clinic was exhausted.
Deviations from the Sample Design
The baseline sampling procedure was aligned to what we proposed in the research proposal.
Only 39 refused to complete data collection, thus the response rate was 98% (2535/2574).
Dates of Data Collection
Muladi and Kalaura
Data Collection Mode
The study employed multiple layers of supervision and quality control. At the most local level, Data International field supervisors directly observed the progress of the data collectors. Data International senior staff also monitored data collection closely. Both Dr. Minhaj Mahmud and three trained supervisors from ICDDR,B performed spot checks of baseline data collection and observed the administration of the BSID–III. AIR home office staff reviewed weekly reports from the field and maintained close communication with the field staff, which was critical to troubleshooting challenges that arose in the field and ensuring the collection of complete and high-quality data.
Data Collection Notes
Data collection took place face to face in the field, using highly scripted surveys. Collectors first located infants in the randomly selected sample by visiting the residential addresses provided by health assistants. After locating each family, the field staff administered the household interview. After completing the survey, the mother was requested to visit her assigned community clinic at her earliest convenience—preferably the following day—so that the BSID–III test could be administered to her child.
DATA International Ltd
Data Collection Manager
DATA International Ltd
Baseline data collection included the following six instruments:
1. Household survey (administered to mothers in every eligible household): The instrument collects information about the household demographic characteristics, household socioeconomic characteristics, knowledge of techniques to stimulate child development, family stimulation behaviors, play and learning activities, child health, feeding practices, and intra-household decision making.
2. Anthropometric measures (administered to all children aged between 3 and 18 months in the study sample): We collected the height, weight, and head circumference of each child.
3. BSID–III test (administered to all children aged between 3 and 18 months in the study sample): The team administered the cognitive and language subscales of the third version of the Bayley Scales of Infant and Toddler Development. This test consists of a series of developmental play tasks that are scored to determine the child’s relative level of development compared with children in the same age cohort. (Appendix A of the Dataset Guide includes copies of all of the study instruments except the Bayley Scales of Infant Development, 3rd Edition, due to copyright restrictions)
4. Service provider survey (administered to health assistants, family welfare assistants, and community health care providers operating in the selected community clinics): These service providers completed a survey that requested information about their demographic characteristics, education and training experiences, primary task and training, workload and job satisfaction. This information is intended to help evaluators identify potential program delivery issues.
5. Administrator survey (administered to district-level health personnel providing information about the inner workings of community clinics and the service providers that these personnel manage): Interviews conducted among the health administrators included: family planning officer, three upazila health and family planning officers, four assistant health inspectors, five health inspectors, one family planning inspector, and one medical technologist.
6. Non-compliance survey (administered to households that refused to participate in this study): The team collected very basic household characteristics to learn about these households.
The first round of data cleaning and checking was carried out at the field level by the field supervisors. Once the hard copies of the completed questionnaires arrived at the data collector’s Dhaka office, the data were entered using customized Microsoft Access software. Statistical check (of, e.g., frequency and range) were conducted to check data consistency and reliability.
Stata files were then sent via secure FTP server to AIR, where they underwent further checking, cleaning, and editing by AIR staff using Stata. Additional variables were derived, as described in the appendix.
Estimates of Sampling Error
American Institutes for Research
Task Team Leader, Education - GP, World Bank
Program Assistant, Education - GP, World Bank
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Use of the dataset must be acknowledged using a citation which would include:
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Marjorie Chinen, American Institutes for Research, Julia Lane, American Institutes for Research. Building Parental Capacity to Help Child Development: A Randomized Controlled Trial of the Save the Children Early Childhood Stimulation Program in Bangladesh 2013-2014, Baseline Survey. Ref. BGD_2013_SCECSPIE-BL_v02_M. Dataset downloaded from [URL] on [date].
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The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.