Pursuant to Local Laws 126, 127, and 128 of 2016, certain demographic data is collected voluntarily and anonymously by persons voluntarily seeking social services. This data can be used by agencies and the public to better understand the demographic makeup of client populations and to better understand and serve residents of all backgrounds and identities. The data presented here has been collected through either electronic form or paper surveys offered at the point of application for services. These surveys are anonymous. Each record represents an anonymized demographic profile of an individual applicant for social services, disaggregated by response option, agency, and program. Response options include information regarding ancestry, race, primary and secondary languages, English proficiency, gender identity, and sexual orientation. Idiosyncrasies or Limitations: Note that while the dataset contains the total number of individuals who have identified their ancestry or languages spoke, because such data is collected anonymously, there may be instances of a single individual completing multiple voluntary surveys. Additionally, the survey being both voluntary and anonymous has advantages as well as disadvantages: it increases the likelihood of full and honest answers, but since it is not connected to the individual case, it does not directly inform delivery of services to the applicant. The paper and online versions of the survey ask the same questions but free-form text is handled differently. Free-form text fields are expected to be entered in English although the form is available in several languages. Surveys are presented in 11 languages. Paper Surveys 1. Are optional 2. Survey taker is expected to specify agency that provides service 2. Survey taker can skip or elect not to answer questions 3. Invalid/unreadable data may be entered for survey date or date may be skipped 4. OCRing of free-form tet fields may fail. 5. Analytical value of free-form text answers is unclear Online Survey 1. Are optional 2. Agency is defaulted based on the URL 3. Some questions must be answered 4. Date of survey is automated
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The STAMINA study examined the nutritional risks of low-income peri-urban mothers, infants and young children (IYC), and households in Peru during the COVID-19 pandemic. The study was designed to capture information through three, repeated cross-sectional surveys at approximately 6 month intervals over an 18 month period, starting in December 2020. The surveys were carried out by telephone in November-December 2020, July-August 2021 and in February-April 2022. The third survey took place over a longer period to allow for a household visit after the telephone interview.The study areas were Manchay (Lima) and Huánuco district in the Andean highlands (~ 1900m above sea level).In each study area, we purposively selected the principal health centre and one subsidiary health centre. Peri-urban communities under the jurisdiction of these health centres were then selected to participate. Systematic random sampling was employed with quotas for IYC age (6-11, 12-17 and 18-23 months) to recruit a target sample size of 250 mother-infant pairs for each survey.Data collected included: household socio-demographic characteristics; infant and young child feeding practices (IYCF), child and maternal qualitative 24-hour dietary recalls/7 day food frequency questionnaires, household food insecurity experience measured using the validated Food Insecurity Experience Scale (FIES) survey module (Cafiero, Viviani, & Nord, 2018), and maternal mental health.In addition, questions that assessed the impact of COVID-19 on households including changes in employment status, adaptations to finance, sources of financial support, household food insecurity experience as well as access to, and uptake of, well-child clinics and vaccination health services were included.This folder includes the dataset and dictionary of variables for survey 3 (English only).The survey questionnaire for survey 3 is available at 10.17028/rd.lboro.21740921.
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A shift in scientific publishing from paper-based to knowledge-based practices promotes reproducibility, machine actionability and knowledge discovery. This is important for disciplines like social science, as study indicators are often social constructs such as race or education; hypothesis tests are challenging to compare in demographic research due to their limited temporal and spatial coverage; and natural language in research papers is often imprecise and ambiguous. Therefore, we present the MIRA-KG, consisting of: (1) an ontology for capturing social demography research, which links hypotheses and findings to evidence, (2) annotations of papers on health inequality in terms of the ontology, gathered by (i) prompting a Large Language Model to annotate paper abstracts using the ontology, (ii) mapping concepts to terms from NCBO BioPortal ontologies and GeoNames, and (iii) refining the final graph by a set of SHACL constraints, developed according to data quality criteria. The utility of the resource lies in its use for formally representing social demography research hypotheses, discovering research biases, discovery of knowledge, and the derivation of novel questions.This dataset was generated using the code available on Github at https://w3id.org/mira/ at version v1.0. It uses the following ontology: https://w3id.org/mira/ontology/.
ALLBUS (GGSS - the German General Social Survey) is a biennial trend survey based on random samples of the German population. Established in 1980, its mission is to monitor attitudes, behavior, and social change in Germany. Each ALLBUS cross-sectional survey consists of one or two main question modules covering changing topics, a range of supplementary questions and a core module providing detailed demographic information. Additionally, data on the interview and the interviewers are provided as well. Key topics generally follow a 10-year replication cycle, many individual indicators and item batteries are replicated at shorter intervals. The present data set contains socio-demographic variables from the ALLBUS 2021, which were harmonized to the standards developed as part of the KonsortSWD sub-project “Harmonized Variables” (Schneider et al., 2023). While there are already established recommendations for the formulation of socio-demographic questionnaire items (e.g. the “Demographic Standards” by Hoffmeyer-Zlotnik et al., 2016), there were no such standards at the variable level. The KonsortSWD project closes this gap and establishes 32 standard variables for 19 socio-demographic characteristics contained in this dataset.
SDES in Kabul was launched in June 2013, jointly by the Central Statistics Organization (CSO) and the United Nations Population Fund (UNFPA) where the latter provided the technical assistance to the entire survey operations. SDES data serve as the benchmark for demographic information at the district level and to some extent, group of villages/enumeration areas. It is the only survey that addresses the need of local development planners for information at the lower level of disaggregation. There are other surveys that CSO has conducted but these are available only at the national and provincial levels.
To achieve a responsive and appropriate policymaking, statistics plays a vital role. In Afghanistan, there has been a longstanding lack of reliable information at the provincial and district levels which hinders the policy making bodies and development planners to come up with comprehensive plans on how to improve the lives of Afghans. With SDES data, though it is not complete yet for the whole country, most of the important indicators in monitoring the progress towards the achievement of Afghanistan's Millennium Development Goals (MDGs) are being collected.
The main objectives of the survey were: · Gathering data for evidence based decision making, policy, planning and management · Providing data for business and industries · Providing policy and planning for residence housing · Providing data about vulnerable populations · Providing data for the basis of humanitarian assistance · Availability of data for research and analysis
Kabul Province Kabul Districts Kabul Villages
Individuals, households
The survey covered all de jure household members (usual residents)
Sample survey data [ssd]
The survey consisted of two related activities: a) the extensive listing and mapping of houses, establishments and institutions (conducted before the household survey) and b) the household survey.
The listing and mapping covered all houses, businesses and institutions in every village and urban area in Kabul Province and included the preparation of sketch maps on which the physical location of each building structure was marked during the canvassing. The locations of important public services, establishments and institutions such as schools, hospitals, banks, etc., were pinpointed using global positioning system (GPS) devices at a later date.
The surveyors used the mapping outputs to guide them in conducting the survey and ensure complete coverage. In total, 16 nahias, and around 843 villages in 14 districts in Kabul Province were canvassed, divided into 3,068 enumeration areas.
The survey first involved a listing of every household in each village. Half of these listed households (i.e. every other household) were taken as samples and asked questions on education, literacy, employment, migration, functional difficulty, fertility, mortality, parents’ living status, birth registration and household and housing characteristics.
Face-to-face [f2f]
Three questionnaires were used to collect the survey data. - Listing sheet for village/enumeration area - Household questionnaire - Summary sheets for village/enumeration area
Central Statistics Organization (CSO) and UNFPA technical staff were responsible for editing the questionnaires, spot-checking, re-interviewing and recording observations during household interviews in all 16 nahias and 14 districts. This helped to ensure errors were corrected at an early stage of enumeration.
Data encoding and cleaning were also done in Karte-char where 178 encoders were hired and four CSO supervisors were detailed to oversee the whole data processing stage.
The primary objective of SASAS is to design, develop and implement a conceptually and methodologically robust study of changing social attitudes and values in South Africa to be able to carefully and consistently monitor and explain changes in attitudes amongst various socio-demographic groupings. The SASAS explores a wide range of value changes, including the distribution and shape of racial attitudes and aspirations, attitudes towards democratic and constitutional issues, and the redistribution of resources and power. Moreover, there is also an explicit interest in mapping changing attitudes towards some of the moral issues that confront and are fiercely debated in South Africa, such as gender issues, AIDS, crime and punishment, governance, and service delivery. The SASAS is intended to provide a unique long-term account of the social fabric of modern South Africa, and of how its changing political and institutional structures interact over time with changing social attitudes and values.
National coverage
The units of analysis in the study are households and individuals
The population under investigation includes adults aged 16 and older in private households in South Africa
Sample survey data [ssd]
Sampling Design The South African Social Attitudes Survey has been designed to yield a representative sample of adults aged 16 and older. The sampling frame for the survey is the Human Sciences Research Council’s (HSRC) Master Sample, which was designed in 2002 and consists of 1 000 primary sampling units (PSUs). The 2001 population census enumerator areas (EAs) were used as PSUs. These PSUs were drawn, with probability proportional to size, from a pre-census 2001 list of EAs provided by Statistics South Africa.
The Master Sample excludes special institutions (such as hospitals, military camps, old age homes, school and university hostels), recreational areas, industrial areas and vacant EAs. It therefore focuses on dwelling units or visiting points as secondary sampling units, which have been defined as ‘separate (non-vacant) residential stands, addresses, structures, flats, homesteads, etc.’.
As the basis of the 2006 SASAS round of interviewing, a sub-sample of 500 PSUs was drawn from the HSRC’s Master Sample. Three explicit stratification variables were used, namely province, geographic type and majority population group.
Within each stratum, the allocated number of PSUs was drawn using proportional to size probability sampling. In each of these drawn PSUs, two clusters of 7 dwelling units each were drawn. These 14 dwelling units in each drawn PSU were systematically grouped into two subsamples of seven, to give the two SASAS samples.
Number of units: Questionnaire 1: 2 497 cases realised from 3 500 addresses; questionnaire 2: 2 483 cases realised from 3 500 addresses; combined : 4980 cases
Face-to-face [f2f]
To accommodate the wide variety of topics that was included in the 2006 survey, two questionnaires were administered simultaneously. Apart from the standard set of demographic and background variables, each version of the questionnaire contained a harmonised core module that remains constant from round to round, with the aim of monitoring change and continuity in a variety of socio-economic and socio-political variables. In addition, a number of themes are accommodated on a rotational basis. This rotating element of the survey consists of two or more topic-specific modules in each round of interviewing and is directed at measuring a range of policy and academic concerns and issues that require more detailed examination at a specific point in time than the multi-topic core module would permit.
Questions for the core module were asked of both samples (3 500 respondents each - 7 000) of which 5 843 realised.
The ISSP module: The International Social Survey Programme (ISSP) is run by a group of research organisations, each of which undertakes to field annually an agreed module of questions on a chosen topic area. SASAS 2003 represents the formalisation of South Africa's inclusion in the ISSP, the intention being to include the module in one of the SASAS questionnaires in each round of interviewing. Each module is chosen for repetition at intervals to allow comparisons both between countries (membership currently stands at 45) and over time. In 2005, the chosen subject was work orientation, and the module was carried in version 2 of the questionnaire (Qs.98-169).
The standard questionnaires dealt with democracy, identity, public services, social values, crime, voting, demographics, families and family authority
Rotating modules: Questionnaire 1: Tourism and leisure, health, poverty and social exclusion, family life, Questionnaire 2: Intergroup relations, media and communication, soccer world cup, work and welfare, ISSP module (role of government), democracy part 2.
The 1998 Ghana Demographic and Health Survey (GDHS) is the latest in a series of national-level population and health surveys conducted in Ghana and it is part of the worldwide MEASURE DHS+ Project, designed to collect data on fertility, family planning, and maternal and child health.
The primary objective of the 1998 GDHS is to provide current and reliable data on fertility and family planning behaviour, child mortality, children’s nutritional status, and the utilisation of maternal and child health services in Ghana. Additional data on knowledge of HIV/AIDS are also provided. This information is essential for informed policy decisions, planning and monitoring and evaluation of programmes at both the national and local government levels.
The long-term objectives of the survey include strengthening the technical capacity of the Ghana Statistical Service (GSS) to plan, conduct, process, and analyse the results of complex national sample surveys. Moreover, the 1998 GDHS provides comparable data for long-term trend analyses within Ghana, since it is the third in a series of demographic and health surveys implemented by the same organisation, using similar data collection procedures. The GDHS also contributes to the ever-growing international database on demographic and health-related variables.
National
Sample survey data
The major focus of the 1998 GDHS was to provide updated estimates of important population and health indicators including fertility and mortality rates for the country as a whole and for urban and rural areas separately. In addition, the sample was designed to provide estimates of key variables for the ten regions in the country.
The list of Enumeration Areas (EAs) with population and household information from the 1984 Population Census was used as the sampling frame for the survey. The 1998 GDHS is based on a two-stage stratified nationally representative sample of households. At the first stage of sampling, 400 EAs were selected using systematic sampling with probability proportional to size (PPS-Method). The selected EAs comprised 138 in the urban areas and 262 in the rural areas. A complete household listing operation was then carried out in all the selected EAs to provide a sampling frame for the second stage selection of households. At the second stage of sampling, a systematic sample of 15 households per EA was selected in all regions, except in the Northern, Upper West and Upper East Regions. In order to obtain adequate numbers of households to provide reliable estimates of key demographic and health variables in these three regions, the number of households in each selected EA in the Northern, Upper West and Upper East regions was increased to 20. The sample was weighted to adjust for over sampling in the three northern regions (Northern, Upper East and Upper West), in relation to the other regions. Sample weights were used to compensate for the unequal probability of selection between geographically defined strata.
The survey was designed to obtain completed interviews of 4,500 women age 15-49. In addition, all males age 15-59 in every third selected household were interviewed, to obtain a target of 1,500 men. In order to take cognisance of non-response, a total of 6,375 households nation-wide were selected.
Note: See detailed description of sample design in APPENDIX A of the survey report.
Face-to-face
Three types of questionnaires were used in the GDHS: the Household Questionnaire, the Women’s Questionnaire, and the Men’s Questionnaire. These questionnaires were based on model survey instruments developed for the international MEASURE DHS+ programme and were designed to provide information needed by health and family planning programme managers and policy makers. The questionnaires were adapted to the situation in Ghana and a number of questions pertaining to on-going health and family planning programmes were added. These questionnaires were developed in English and translated into five major local languages (Akan, Ga, Ewe, Hausa, and Dagbani).
The Household Questionnaire was used to enumerate all usual members and visitors in a selected household and to collect information on the socio-economic status of the household. The first part of the Household Questionnaire collected information on the relationship to the household head, residence, sex, age, marital status, and education of each usual resident or visitor. This information was used to identify women and men who were eligible for the individual interview. For this purpose, all women age 15-49, and all men age 15-59 in every third household, whether usual residents of a selected household or visitors who slept in a selected household the night before the interview, were deemed eligible and interviewed. The Household Questionnaire also provides basic demographic data for Ghanaian households. The second part of the Household Questionnaire contained questions on the dwelling unit, such as the number of rooms, the flooring material, the source of water and the type of toilet facilities, and on the ownership of a variety of consumer goods.
The Women’s Questionnaire was used to collect information on the following topics: respondent’s background characteristics, reproductive history, contraceptive knowledge and use, antenatal, delivery and postnatal care, infant feeding practices, child immunisation and health, marriage, fertility preferences and attitudes about family planning, husband’s background characteristics, women’s work, knowledge of HIV/AIDS and STDs, as well as anthropometric measurements of children and mothers.
The Men’s Questionnaire collected information on respondent’s background characteristics, reproduction, contraceptive knowledge and use, marriage, fertility preferences and attitudes about family planning, as well as knowledge of HIV/AIDS and STDs.
A total of 6,375 households were selected for the GDHS sample. Of these, 6,055 were occupied. Interviews were completed for 6,003 households, which represent 99 percent of the occupied households. A total of 4,970 eligible women from these households and 1,596 eligible men from every third household were identified for the individual interviews. Interviews were successfully completed for 4,843 women or 97 percent and 1,546 men or 97 percent. The principal reason for nonresponse among individual women and men was the failure of interviewers to find them at home despite repeated callbacks.
Note: See summarized response rates by place of residence in Table 1.1 of the survey report.
The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors, and (2) sampling errors. Nonsampling errors are the results of shortfalls made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 1998 GDHS to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.
Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 1998 GDHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.
A sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95 percent of all possible samples of identical size and design.
If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 1998 GDHS sample is the result of a two-stage stratified design, and, consequently, it was necessary to use more complex formulae. The computer software used to calculate sampling errors for the 1998 GDHS is the ISSA Sampling Error Module. This module uses the Taylor linearization method of variance estimation for survey estimates that are means or proportions. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.
Data Quality Tables - Household age distribution - Age distribution of eligible and interviewed women - Age distribution of eligible and interviewed men - Completeness of reporting - Births by calendar years - Reporting of age at death in days - Reporting of age at death in months
Note: See detailed tables in APPENDIX C of the survey report.
Description: The questions contained in SASAS questionnaires one and two for 2008 were asked of a half sample of approximately 3500 respondents each.
The data set contains 3292 records and 264 variables.
Topics included in the questionnaires are: demographics and other classificatory variables.
Rotating modules are: International Social Surveys Programme (ISSP) module: religion, traditional belief, water and sanitation, hunger scale. Abstract: The primary objective of the South African Social Attitudes Survey (SASAS) is to design, develop and implement a conceptually and methodologically robust study of changing social attitudes and values in South Africa. In meeting this objective, the HSRC is carefully and consistently monitoring and providing insight into changes in attitudes among various socio-demographic groupings. SASAS is intended to provide a unique long-term account of the social fabric of modern South Africa, and of how its changing political and institutional structures interact over time with changing social attitudes and values.
The survey has been designed to yield a national representative sample of adults aged 16 and older, using the Human Sciences Research Council's (HSRC) second Master Sample, which was designed in 2007 and consists of 1000 primary sampling units (PSUs). These PSUs were drawn, with probability proportional to size from a pre-census 2001 list of 80780 enumerator areas (EAs).
As the basis of the 2008 SASAS round of interviewing, a sub-sample of 500 EAs (PSUs) was drawn from the second master sample. Three explicit stratification variables were used, namely province, geographic type and majority population group. The survey is conducted annually and the 2008 survey is the sixth wave in the series.
To accommodate the wide variety of topics included in the survey, two questionnaires are administered simultaneously.
The core module will remain constant for subsequent annual SASAS surveys with the aim of monitoring change and continuity in a variety of socio-economic and socio-political variables. In addition, a number of themes will be accommodated in rotation. The rotating element of the survey consists of two or more topic-specific modules in each round of interviewing and is directed at measuring a range of policy and academic concerns and issues that require more detailed examination at a specific point in time than the multi-topic core module would permit. The two different versions of the questionnaire were administered concurrently in each of the chosen sampling areas.
Fieldworkers were required to complete a paper-based instrument while interviews were conducted face-to-face.
Topics included in the questionnaires are: democracy, national identity and pride, education, moral issues, crime, voting, demographics and other classificatory variables.
Rotating modules are: intergroup relations, gender attitudes, poverty, household expenditure, Soccer World Cup, service delivery, Hope Scale, water and sanitation and Hunger Scale.
International Social Survey Programme. (ISSP web page:www.issp.org/)
The International Social Survey Programme (ISSP) is run by a group of research organisations, each of which undertakes to field annually an agreed module of questions on a chosen topic area. SASAS 2003 represents the formalisation of South Africa's inclusion in the ISSP, the intention being to include the module in one of the SASAS questionnaires in each round of interviewing. Each module is chosen for repetition at intervals to allow comparisons both between countries (membership currently stands at 48) and over time. In 2008, the chosen subject was the religion and the module was carried in version two of the questionnaire (Qs.1-80. This data can be accessed through the ISSP data portal (see link above).
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Parenthood can be defined by the contradiction that it is one of the most satisfying yet stressful experiences in life. Many parents experience stress during parenthood, and some to the extent that they display symptoms of parental burnout. Nevertheless, research on parental burnout is scant and many studies have only examined the condition in Western settings. The aim of this study was to examine parental burnout among Somali mothers in Mogadishu, Somalia, and its association with certain psychological, psychosocial, and sociodemographic factors. In this cross-sectional study, questionnaire data were collected through the measurements Parental Burnout Assessment and Patient Health Questionnaire 9, as well as through social and demographic questions. A total of 882 Somali mothers in Mogadishu participated. The analysis methods used were univariate, bivariate, and multiple linear regression analysis. The results revealed that the mean parental burnout score was low in the sample. Additionally, a significant association was found between higher levels of parental burnout and higher levels of depression, perceived lack of social support, being unmarried, having a low monthly household income, and when the youngest child was of school-age.
The Gallup Poll Social Series (GPSS) is a set of public opinion surveys designed to monitor U.S. adults' views on numerous social, economic, and political topics. The topics are arranged thematically across 12 surveys. Gallup administers these surveys during the same month every year and includes the survey's core trend questions in the same order each administration. Using this consistent standard allows for unprecedented analysis of changes in trend data that are not susceptible to question order bias and seasonal effects.
Introduced in 2001, the GPSS is the primary method Gallup uses to update several hundred long-term Gallup trend questions, some dating back to the 1930s. The series also includes many newer questions added to address contemporary issues as they emerge.
The dataset currently includes responses from up to and including 2025.
Gallup conducts one GPSS survey per month, with each devoted to a different topic, as follows:
January: Mood of the Nation
February: World Affairs
March: Environment
April: Economy and Finance
May: Values and Beliefs
June: Minority Rights and Relations (discontinued after 2016)
July: Consumption Habits
August: Work and Education
September: Governance
October: Crime
November: Health
December: Lifestyle (conducted 2001-2008)
The core questions of the surveys differ each month, but several questions assessing the state of the nation are standard on all 12: presidential job approval, congressional job approval, satisfaction with the direction of the U.S., assessment of the U.S. job market, and an open-ended measurement of the nation's "most important problem." Additionally, Gallup includes extensive demographic questions on each survey, allowing for in-depth analysis of trends.
Interviews are conducted with U.S. adults aged 18 and older living in all 50 states and the District of Columbia using a dual-frame design, which includes both landline and cellphone numbers. Gallup samples landline and cellphone numbers using random-digit-dial methods. Gallup purchases samples for this study from Survey Sampling International (SSI). Gallup chooses landline respondents at random within each household based on which member had the next birthday. Each sample of national adults includes a minimum quota of 70% cellphone respondents and 30% landline respondents, with additional minimum quotas by time zone within region. Gallup conducts interviews in Spanish for respondents who are primarily Spanish-speaking.
Gallup interviews a minimum of 1,000 U.S. adults aged 18 and older for each GPSS survey. Samples for the June Minority Rights and Relations survey are significantly larger because Gallup includes oversamples of Blacks and Hispanics to allow for reliable estimates among these key subgroups.
Gallup weights samples to correct for unequal selection probability, nonresponse, and double coverage of landline and cellphone users in the two sampling frames. Gallup also weights its final samples to match the U.S. population according to gender, age, race, Hispanic ethnicity, education, region, population density, and phone status (cellphone only, landline only, both, and cellphone mostly).
Demographic weighting targets are based on the most recent Current Population Survey figures for the aged 18 and older U.S. population. Phone status targets are based on the most recent National Health Interview Survey. Population density targets are based on the most recent U.S. Census.
The year appended to each table name represents when the data was last updated. For example, January: Mood of the Nation - 2025** **has survey data collected up to and including 2025.
For more information about what survey questions were asked over time, see the Supporting Files.
Data access is required to view this section.
The 2013 Turkey Demographic and Health Survey (TDHS-2013) is a nationally representative sample survey. The primary objective of the TDHS-2013 is to provide data on socioeconomic characteristics of households and women between ages 15-49, fertility, childhood mortality, marriage patterns, family planning, maternal and child health, nutritional status of women and children, and reproductive health. The survey obtained detailed information on these issues from a sample of women of reproductive age (15-49). The TDHS-2013 was designed to produce information in the field of demography and health that to a large extent cannot be obtained from other sources.
Specifically, the objectives of the TDHS-2013 included: - Collecting data at the national level that allows the calculation of some demographic and health indicators, particularly fertility rates and childhood mortality rates, - Obtaining information on direct and indirect factors that determine levels and trends in fertility and childhood mortality, - Measuring the level of contraceptive knowledge and practice by contraceptive method and some background characteristics, i.e., region and urban-rural residence, - Collecting data relative to maternal and child health, including immunizations, antenatal care, and postnatal care, assistance at delivery, and breastfeeding, - Measuring the nutritional status of children under five and women in the reproductive ages, - Collecting data on reproductive-age women about marriage, employment status, and social status
The TDHS-2013 information is intended to provide data to assist policy makers and administrators to evaluate existing programs and to design new strategies for improving demographic, social and health policies in Turkey. Another important purpose of the TDHS-2013 is to sustain the flow of information for the interested organizations in Turkey and abroad on the Turkish population structure in the absence of a reliable and sufficient vital registration system. Additionally, like the TDHS-2008, TDHS-2013 is accepted as a part of the Official Statistic Program.
National coverage
The survey covered all de jure household members (usual residents), children age 0-5 years and women age 15-49 years resident in the household.
Sample survey data [ssd]
The sample design and sample size for the TDHS-2013 makes it possible to perform analyses for Turkey as a whole, for urban and rural areas, and for the five demographic regions of the country (West, South, Central, North, and East). The TDHS-2013 sample is of sufficient size to allow for analysis on some of the survey topics at the level of the 12 geographical regions (NUTS 1) which were adopted at the second half of the year 2002 within the context of Turkey’s move to join the European Union.
In the selection of the TDHS-2013 sample, a weighted, multi-stage, stratified cluster sampling approach was used. Sample selection for the TDHS-2013 was undertaken in two stages. The first stage of selection included the selection of blocks as primary sampling units from each strata and this task was requested from the TURKSTAT. The frame for the block selection was prepared using information on the population sizes of settlements obtained from the 2012 Address Based Population Registration System. Settlements with a population of 10,000 and more were defined as “urban”, while settlements with populations less than 10,000 were considered “rural” for purposes of the TDHS-2013 sample design. Systematic selection was used for selecting the blocks; thus settlements were given selection probabilities proportional to their sizes. Therefore more blocks were sampled from larger settlements.
The second stage of sample selection involved the systematic selection of a fixed number of households from each block, after block lists were obtained from TURKSTAT and were updated through a field operation; namely the listing and mapping fieldwork. Twentyfive households were selected as a cluster from urban blocks, and 18 were selected as a cluster from rural blocks. The total number of households selected in TDHS-2013 is 14,490.
The total number of clusters in the TDHS-2013 was set at 642. Block level household lists, each including approximately 100 households, were provided by TURKSTAT, using the National Address Database prepared for municipalities. The block lists provided by TURKSTAT were updated during the listing and mapping activities.
All women at ages 15-49 who usually live in the selected households and/or were present in the household the night before the interview were regarded as eligible for the Women’s Questionnaire and were interviewed. All analysis in this report is based on de facto women.
Note: A more technical and detailed description of the TDHS-2013 sample design, selection and implementation is presented in Appendix B of the final report of the survey.
Face-to-face [f2f]
Two main types of questionnaires were used to collect the TDHS-2013 data: the Household Questionnaire and the Individual Questionnaire for all women of reproductive age. The contents of these questionnaires were based on the DHS core questionnaire. Additions, deletions and modifications were made to the DHS model questionnaire in order to collect information particularly relevant to Turkey. Attention also was paid to ensuring the comparability of the TDHS-2013 findings with previous demographic surveys carried out by the Hacettepe Institute of Population Studies. In the process of designing the TDHS-2013 questionnaires, national and international population and health agencies were consulted for their comments.
The questionnaires were developed in Turkish and translated into English.
TDHS-2013 questionnaires were returned to the Hacettepe University Institute of Population Studies by the fieldwork teams for data processing as soon as interviews were completed in a province. The office editing staff checked that the questionnaires for all selected households and eligible respondents were returned from the field. A total of 29 data entry staff were trained for data entry activities of the TDHS-2013. The data entry of the TDHS-2013 began in late September 2013 and was completed at the end of January 2014.
The data were entered and edited on microcomputers using the Census and Survey Processing System (CSPro) software. CSPro is designed to fulfill the census and survey data processing needs of data-producing organizations worldwide. CSPro is developed by MEASURE partners, the U.S. Bureau of the Census, ICF International’s DHS Program, and SerPro S.A. CSPro allows range, skip, and consistency errors to be detected and corrected at the data entry stage. During the data entry process, 100% verification was performed by entering each questionnaire twice using different data entry operators and comparing the entered data.
In all, 14,490 households were selected for the TDHS-2013. At the time of the listing phase of the survey, 12,640 households were considered occupied and, thus, eligible for interview. Of the eligible households, 93 percent (11,794) households were successfully interviewed. The main reasons the field teams were unable to interview some households were because some dwelling units that had been listed were found to be vacant at the time of the interview or the household was away for an extended period.
In the interviewed 11,794 households, 10,840 women were identified as eligible for the individual interview, aged 15-49 and were present in the household on the night before the interview. Interviews were successfully completed with 9,746 of these women (90 percent). Among the eligible women not interviewed in the survey, the principal reason for nonresponse was the failure to find the women at home after repeated visits to the household.
The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors, and (2) sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the TDHS-2013 to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.
Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the TDHS-2013 is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.
A sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall
Socio-economic and demographic questions. Demography: sex; age; marital status; household size; main breadwinner; education; employment status, occupation and industry of the respondent and the main breadwinner; instruction and payment of other people; judgement on household´s standard of living; monthly net household income. Additionally coded was: questionnaire-ID; settlement; region. Sozioökonomische und demographische Fragen. Demographie: Geschlecht; Alter; Familienstand; Haushaltsgröße; Hauptverdiener; höchster Bildungsabschluss des Befragten und des Hauptverdieners; derzeitiger Erwerbsstatus des Befragten und des Hauptverdieners; Beruf und Branche des Befragten und des Hauptverdieners; Weisungsbefugnis; Entlohnung Dritter; Beurteilung des Lebensstandards des Haushalts; Haushaltsnettoeinkommen (kategorisiert). Zusätzlich verkodet wurde: Fragebogen-ID; Urbanisierungsgrad des Wohnortes; Region. Probability Sample: Multistage Sample Wahrscheinlichkeitsauswahl: Mehrstufige Zufallsauswahl Face-to-face interview: PAPI (Paper and Pencil Interview) Persönliches Interview: PAPI (Papierfragebogen)
The Cambodia Demographic and Health Survey in 2010 (CDHS 2010) is the third nationally representative survey conducted in Cambodia on population and health issues. It uses the same methodology as its predecessors, the 2000 and the 2005 Cambodia Demographic and Health Surveys, allowing policymakers to use these surveys to assess trends over time. The primary objective of the CDHS is to provide the Ministry of Health (MOH), Ministry of Planning (MOP), and other relevant institutions and users with updated and reliable data on infant and child mortality, fertility preferences, family planning behavior, maternal mortality, utilization of maternal and child health services, health expenditures, women’s status, and knowledge and behavior regarding HIV/AIDS and other sexually transmitted infections. This information contributes to policy decisions, planning, monitoring, and program evaluation for the development of Cambodia at both the national and local government levels.
The sample was designed to provide estimates of the indicators at the national level, for urban and rural areas, and for 19 domains: 1. Banteay Mean Chey 2. Kampong Cham 3. Kampong Chhnang 4. Kampong Speu 5. Kampong Thom 6. Kandal 7. Phnom Penh 8. Prey Veng 9. Pursat 10. Svay Rieng 11. Takeo 12. Kratie 13. Siem Reap 14. Otdar Mean Chey 15. Battambang and Krong Pailin 16. Kampot and Krong Kep 17. Krong Preah Sihanouk and Kaoh Kong 18. Preah Vihear and Steng Treng 19. Mondol Kiri and Rattanak Kiri
Household, individual (including women and men between the ages of 15 and 49), and children aged 5 and below.
The survey covered the whole resident population (regular household) , with the exception of homeless in Cambodia
Sample survey data
The survey was based on a stratified sample selected in two stages. Stratification was achieved by separating every reporting domain into urban and rural areas. Thus, the 19 domains. Samples were selected independently in every stratum through a two-stage selection process. Implicit stratifications were achieved at each of the lower geographical or administrative levels by sorting the sampling frame according to geographical/administrative order and by using a probability proportional to size selection strategy at the first stage of selection. (Please refer to technical doccuments for details).
Face-to-face
There are three types of questionnaires used in the CDHS: the Household Questionnaire, the Individual Woman's Questionnaire, and the Individual Man's Questionnaire.
The households that have been scientifically selected to be included in the CDHS sample were visited and interviewed using a Household Questionnaire. The Household Questionnaire consisted of a cover sheet to identify the household and a form on which all members of the household and visitors were listed. Data collected about each household member were name, sex, age, education, and survival of parents for children under age 18 years, etc. The Household Questionnaire was used to collect information on housing characteristics such as type of water, sanitation facilities, quality of flooring, and ownership of durable goods.
The Household Questionnaire permitted the interviewer to identify women and men who were eligible for the Individual Questionnaire. Women ages 15-49 years in every selected household who are members of the household (those that usually live in the household) and visitors (those who do not usually live in the household but who slept there the previous night) were eligible to be interviewed with the individual Woman's Questionnaire.
After all of the eligible women in a household have been identified, female interviewers used the Woman's Questionnaire to interview the women. The Woman's Questionnaire collected information on the following topics:
- socio-demographic characteristics
- reproduction
- birth spacing
- maternal health care and breastfeeding
- immunization and health of children
- cause of death of children
- marriage and sexual activity
- fertility preferences
- characteristics of the husband and employment activity of the woman
- HIV
- maternal mortality
- women's status
- household relations
In one-half of the households, men were identified as eligible for individual interview, and the male interviewer of each team used the Man's Questionnaire to interview the eligible men. Team leaders informed their teams which households in the sample have been selected for including interviews with men. The Man's Questionnaire collected information on the following topics:
- socio-demographic characteristics
- reproduction
- birth spacing
- marriage and sexual activity
- HIV
Biomarker data collection were conducted in the same one-half of the households which were selected to include men for interview. The biomarker data collection included: measuring the height and weight of women and children (under age 6 years), anemia testing of women and children, and drawing blood samples from women and men for laboratory testing of HIV. Biomarker data collection were recorded in the Household Questionnaire.
The data processing activities of the survey involved manual and automatic processes that had a direct impact on the quality of the data.
The data entry for the DHS survey was carried out using the software package CSPro. The DHS questionnaires were entered by cluster, with each cluster being assigned to one data entry operator. The data for each cluster were entered into a separate data file for that cluster to protect against a major loss of data due to hardware or software failure. Below is a list of the main processes involved in data processing:
a. Office editing and coding - minimal since CSPro has been designed to be an intelligent data entry program b. Data entry c. Completeness of data file d. Verification of Data - prior to this stage, data are again entered and tagged as V to indicate that the dataset is a verification data e. Secondary editing
Response rate:
Households: 99 per cent Women ages 15-49: 98 per cent Men ages 15-49: 95 per cent
See Table 1. Results of the household and individual interviews in the CDHS 2010 Preliminary Report
The computer software used to calculate sampling errors for the 2010 CDHS is a Macro SAS procedure. This procedure used the Taylor linearization method for variance estimation for survey estimates that are means or proportions. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates. ISSA also computes ISSA computes the design effect (DEFT) for each estimate.
Sampling errors for the 2010 CDHS are calculated for selected variables considered to be of primary interest for woman’s survey and for man’s surveys, respectively for the country as a whole, for urban and rural areas, and for each of the 19 study domains.
Abstract copyright UK Data Service and data collection copyright owner.
The Citizenship Survey (known in the field as the Communities Study) ran from 2001 to 2010-2011. It began as the 'Home Office Citizenship Survey' (HOCS) before the responsibility moved to the new Communities and Local Government department (DCLG) in May 2006. The survey provided an evidence base for the work of DCLG, principally on the issues of community cohesion, civic engagement, race and faith, and volunteering. The survey was used extensively for developing policy and for performance measurement. It was also used more widely, by other government departments and external stakeholders to help inform their work around the issues covered in the survey. The survey was conducted on a biennial basis from 2001-2007. It moved to a continuous design in 2007 which means that data became available on a quarterly basis from April of that year. Quarter one data were collected between April and June; quarter two between July and September; quarter three between October and December and quarter four between January and March. Once collection for the four quarters was completed, a full aggregated dataset was made available, and the larger sample size allowed more detailed analysis.Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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BackgroundBangladesh is one of the most densely populated countries in the world, with more than one-third of its people living in cities, and its air quality is among the worst in the world. The present study aimed to measure knowledge, attitudes and practice (KAP) towards air pollution and health effects among the general population living in the large cities in Bangladesh.MethodsA cross-sectional e-survey was conducted between May and July 2022 among eight divisions in Bangladesh. A convenience sampling technique was utilized to recruit a total of 1,603 participants (55.58% males; mean age: 23.84 ± 5.93 years). A semi-structured questionnaire including informed consent, socio-demographic information, as well as questions regarding knowledge (11-item), attitudes (7-item) and practice (11-item) towards air pollution, was used to conduct the survey. All analyses (descriptive statistics and regression analyses) were performed using STATA (Version 15.0) and SPSS (Version 26.0).ResultsThe mean scores of the knowledge, attitudes, and practice were 8.51 ± 2.01 (out of 11), 19.24 ± 1.56 (out of 21), and 12.65 ±5.93 (out of 22), respectively. The higher scores of knowledge, attitudes, and practice were significantly associated with several socio-demographic factors, including educational qualification, family type, residential division, cooking fuel type, etc.ConclusionsThe present study found a fair level of knowledge and attitudes towards air pollution; however, the level of practice is not particularly noteworthy. The finding suggests the need to create more awareness among the general population to increase healthy practice to reduce the health effects of air pollution.
Abstract copyright UK Data Service and data collection copyright owner.
The British Gambling Prevalence Survey is a large-scale nationally representative survey of participation in gambling and the prevalence of problem gambling in Great Britain.https://borealisdata.ca/api/datasets/:persistentId/versions/7.1/customlicense?persistentId=doi:10.7939/DVN/10004https://borealisdata.ca/api/datasets/:persistentId/versions/7.1/customlicense?persistentId=doi:10.7939/DVN/10004
The Population Research Laboratory (PRL), a member of the Association of Academic Survey Research Organizations (AASRO), seeks to advance the research, education and service goals of the University of Alberta by helping academic researchers and policy makers design and implement applied social science research projects. The PRL specializes in the gathering, analysis, and presentation of data about demographic, social and public issues. The PRL research team provides expert consultation and implementation of quantitative and qualitative research methods, project design, sample design, web-based, paper-based and telephone surveys, field site testing, data analysis and report writing. The PRL follows scientifically rigorous and transparent methods in each phase of a research project. Research Coordinators are members of the American Association for Public Opinion Research (AAPOR) and use best practices when conducting all types of research. The PRL has particular expertise in conducting computer-assisted telephone interviews (referred to as CATI surveys). When conducting telephone surveys, all calls are displayed as being from the "U of A PRL", a procedure that assures recipients that the call is not from a telemarketer, and thus helps increase response rates. The PRL maintains a complement of highly skilled telephone interviewers and supervisors who are thoroughly trained in FOIPP requirements, respondent selection procedures, questionnaire instructions, and neutral probing. A subset of interviewers are specially trained to convince otherwise reluctant respondents to participate in the study, a practice that increases response rates and lowers selection bias. PRL staff monitors data collection on a daily basis to allow any necessary adjustments to the volume and timing of calls and respondent selection criteria. The Population Research Laboratory (PRL) administered the 2012 Alberta Survey B. This survey of households across the province of Alberta continues to enable academic researchers, government departments, and non-profit organizations to explore a wide range of topics in a structured research framework and environment. Sponsors' research questions are asked together with demographic questions in a telephone interview of Alberta households. This data consists of the information from 1207 Alberta residence, interviewed between June 5, 2012 and June 27, 2012. The amount of responses indicates that the response rate, as calculated percentages representing the number of people who participated in the survey divided by the number selected in the eligible sample, was 27.6% for survey B. The subject ares included in the 2012 Alberta Survey B includes socio-demographic and background variables such as: household composition, age, gender, marital status, highest level of education, household income, religion, ethnic background, place of birth, employment status, home ownership, political party support and perceptions of financial status. In addition, the topics of public health and injury control, tobacco reduction, activity limitations and personal directives, unions, politics and health.
Full edition for scientific use. Since 1983 labour force surveys (LFS) are conducted annually in all European Union (EU) member states. The LFS serve as a basis for internationally compatible (in terms of definition and survey method) data on employment and unemployment for the European Commission. In Austria, the LFS is conducted in full annually. The chosen month therefore is March because in this month the Microcensus quarterly-survey which is most suitable in terms of scheduling for the LFS is performed. Central questions for the assessment of the number of employed and unemployed persons (and as a result for the calculation of the unemployment rate according to international standards) are in addition (since 1994) asked quarterly in the Microcensus standard survey. The survey conducted in March always relates to the week before the interview and includes the whole population, which means everybody who has their main residence in Austria. Data for persons not found have to be added via a substitution method so that results for the whole population can be provided. In Austria (as well as in several other states), the LFS is only conducted among the population in private households; people who live in institutions (retirement homes, boarding homes, etc.) are not included in the survey. These are topics of the LFS: -> immigrants with and without the Austrian citizenship (4 questions) -> features of the first job (21 questions) -> statements on part-time jobs (6 questions) -> previous employments of unemployed persons (7 questions) -> job-seeking (13 questions) -> situation of unemployed persons (3 questions) -> school and professional education (9 questions) -> situation one year previous to the survey (7 questions). Furthermore, there are questions on the socio-demographic background. The questions have remained more or less the same over the years. The only questions that have been changed slightly were those on education. Missing information is substituted with information from persons with similar socio-demographic variables (imputation), so that there are no unknown cases.
The objectives of the 2001 Ethiopia Stand-alone Child Lobour Survey was to provide Statistical data on children's activities focusing on the status of schooling non-economic and economic activities. Specifically, the Survey was aimed at to provide statistical data that will help to: (a) establish the demographic and socio-economic characteristics of children: age, sex, status and levels of education and training occupations, skill-levels, hours of work, earnings and other working and living conditions; (b) assess the working situation of children and the influence on their education, health physical and mental development; (c) examine the characteristics of the sectors that employ most children; (d) identify where and how long the children have been working and the factors that lead children to work or families to put children to work and; (e) assess the health and welfare status of working children.
The survey collected information for all members of selected households as well as for children aged 5-17 years. Data collected for all members of the household include particulars of household members, like age, sex, religion, ethnicity, school attendance and training and marital status; economic activity status of the population aged 5 years and over during the last seven days, if non-working (economically and active) reason for not working, number of hours worked, ... etc.; economic activities of population aged 10 years and over during the last twelve months; housing conditions, housing facilities and household income and expenditure were collected.
For children aged 5-17 years, information on movement of children between households; school attendance and reason for dropouts; domestic activities and idleness; health and welfare situations of children who have been working at any time in the past; conditions of employment of children who are working for a non-relative person for pay; perception of parents of those children that are engaged in economic activity about the children’s working conditions were collected from their parents or guardians. Similar information about children aged 10-17 years were also collected from children themselves.
National coverage
The survey is not covered non-sedentary areas of two zones of the Affar Region and six zones of the Somali Region. Residents of collective quarters, homeless and foreigners were not covered in the survey.
Sample survey data [ssd]
Sampling Frame: The Enumeration Area (EA) delineated for the 1994 Population and Housing Census of Ethiopia was used as a sampling frame for the selection of Primary Sampling Units (PSU). The sampling frame used for the selection f ultimate sampling units (households) as a fresh list of households, which was prepared b y the enumerator in the sampled E A at the time of the survey.
Sample Design: The 2001 Stand-alone National Child Labour Survey of Ethiopia covered both rural and urban parts of the country. However, it has not covered non-sedentary areas of two zones of the Affar Region and six zones of the Somali Region. Residents of collective quarters, homeless and foreigners were not covered in the survey. For the purpose of the survey, the population of the country was divided into three major categories namely, rural, major urban centers and other urban centers.
Category I: Rural parts of each regional state were grouped in this category. Each of the regions was a reporting level: thus, there are 11 reporting levels in this category.
Category II: Major urban centers were grouped under this category. The list of urban centers included in this category (domain of study). Each of them were used as the survey domains for which the survey results were reported, hence, the reporting levels under this category are totally 11 major urban centers, namely, Mekele, Gonder, Dessie, Bahir Dar, Nazreth, Debre Zeit, Jimma, Awassa, Harar, Addis Ababa and DireDawa.
Category III: Other urban centers, which were not included in category II, were included in this category. Except for Harari Region, Addis Ababa and Dire Dawa administrations, each region was serving as a reporting level independently by their respective regional states. As we can see from Table 2.3 this category has 8 reporting levels.
In addition to the above domains of study, the survey results were also reported at regional and country levels by aggregating the survey results from the corresponding domains. All in all 48 basic survey domains (reporting levels) including urban part of each regional state, total (urban + rural) part of each region, country level urban, country level rural and country level total were defined for the survey.
Sample Size Selection Schema: A sample size of 1,257 EAs was fixed based upon the required precision level and available resource for the survey. The 1999 National Labor Force Survey result was used to determine the required number of sample households per PSU/EA. For this survey, it was found that about 35 households per EA would give fair and reasonable estimates at a required reporting level for the variables under study.
In category II, and I stratified two-stage cluster sampling was used for the selection of ultimate sampling units. The Primary Sampling Units (PSUs) are EAs and secondary sampling units are households. In category III stratified three-stages cluster sampling was used for the selection of ultimate sampling units. In this category the PSUs are towns, the Secondary Sampling Units (SSUs) are EAs and the tertiary sampling units are households t he probability proportional to size (PPS) systematic sampling, size being total number of households obtained from the 1994 population and housing census was used for selection of towns and E As.
From category I a total of 723 EAs, from category II a total of 305 EAs and from category III a total of 229 EAs were selected after generating afresh listing of households within each sample EA at the beginning of the field work the survey questionnaire was administered to 35 systematically selected households for rural and both categories of the urban domains. Based on the results of the survey coverage rate of sample EAs was 100 percent and response rate of sampled household was 99.1percent.
Face-to-face [f2f]
At the inception of the survey design, the ILO has provided the Central Statistical Authority (CSA) a draft module questionnaire that was tested and applied in other African countries to be used as a base and to decide on the content and format of the Ethiopia Stand-alone Child Labour Survey. The ILO's module questionnaire was then redesigned to reflect the existing conditions of the country, in close consultation with Ministry of Labour and Social Affairs (MOLSA) and the ILO in order to satisfy the data requirements of the country as well as the feasibility in the data collection operations. Accordingly, the survey questionnaire modified into three forms, where Form-I of the questionnaire that refers to demographic and socio-economic condition of household members was administered to each member of the selected households. Form-II of the survey questionnaire refers to children aged 5-17 years and the information was collected by interviewed from the parents or guardians of the children, while Form-III was addressed to children aged 10-17 years and the children themselves give the responses to the questions.
In the process of designing the survey questionnaire, a pilot survey was conducted where the questionnaires and other survey instruments were tested in the field and amended accordingly. Furthermore, a half day user-producer forum was prepared that involved the Ministry of Labour and Social Affairs, other concerned government agencies, the ILO Area Office in Addis Ababa and NGO's that are involved in child issues. Comments and inputs on the draft content of the survey questionnaire from the users aspect were obtained and are used as inputs in finalizing the questionnaire.
Briefly the major variables included in the three Forms of the questionnaire are presented below.
Form - I: Area Identification of the Selected Household and Socio-demographic Characteristics of Household Members
Section 1: Area identification of the selected household.
Section 2: Particulars of respondents and household members, that is, socio-demographic characteristics of the population like age, sex, religion, ethnicity, schooling and training and marital status.
Section 3: Economic activities of the population aged 5 years and over during the last seven days; this section identifies working and non-working population and reason for not working, number of hours worked, amount and source of earnings of children as well as other members of household.
Section 4: Economic activities of population aged 10 years and over during the last twelve months.
Section 5: Household section of the questionnaire that deals with housing conditions, housing facilities and household income and expenditure.
Form - II: Economic Activity Status of Children Aged 5-17 Years - to be addressed to Parents, Guardians or Heads of Households Section 6: Movement of children between households; Section 7: Schooling and reason for dropouts; Section 8: Domestic activities without payment and idleness; Section 9: Health and welfare situations of children who have been working at any time in the past; Section 10: Conditions of employment of children who are working for a non-relative person for pay; Section 11: Perception of parents of those children that
Ipsos Global @dvisor wave 29 was conducted on January 3 and January 16, 2012. It included the following question sections: A: Demographic Profile, B: Consumer Confidence, R: Reuters Battery, DY: Social Media Survey, EB: Eurozone Questions.
Pursuant to Local Laws 126, 127, and 128 of 2016, certain demographic data is collected voluntarily and anonymously by persons voluntarily seeking social services. This data can be used by agencies and the public to better understand the demographic makeup of client populations and to better understand and serve residents of all backgrounds and identities. The data presented here has been collected through either electronic form or paper surveys offered at the point of application for services. These surveys are anonymous. Each record represents an anonymized demographic profile of an individual applicant for social services, disaggregated by response option, agency, and program. Response options include information regarding ancestry, race, primary and secondary languages, English proficiency, gender identity, and sexual orientation. Idiosyncrasies or Limitations: Note that while the dataset contains the total number of individuals who have identified their ancestry or languages spoke, because such data is collected anonymously, there may be instances of a single individual completing multiple voluntary surveys. Additionally, the survey being both voluntary and anonymous has advantages as well as disadvantages: it increases the likelihood of full and honest answers, but since it is not connected to the individual case, it does not directly inform delivery of services to the applicant. The paper and online versions of the survey ask the same questions but free-form text is handled differently. Free-form text fields are expected to be entered in English although the form is available in several languages. Surveys are presented in 11 languages. Paper Surveys 1. Are optional 2. Survey taker is expected to specify agency that provides service 2. Survey taker can skip or elect not to answer questions 3. Invalid/unreadable data may be entered for survey date or date may be skipped 4. OCRing of free-form tet fields may fail. 5. Analytical value of free-form text answers is unclear Online Survey 1. Are optional 2. Agency is defaulted based on the URL 3. Some questions must be answered 4. Date of survey is automated