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Professional organizations in STEM (science, technology, engineering, and mathematics) can use demographic data to quantify recruitment and retention (R&R) of underrepresented groups within their memberships. However, variation in the types of demographic data collected can influence the targeting and perceived impacts of R&R efforts - e.g., giving false signals of R&R for some groups. We obtained demographic surveys from 73 U.S.-affiliated STEM organizations, collectively representing 712,000 members and conference-attendees. We found large differences in the demographic categories surveyed (e.g., disability status, sexual orientation) and the available response options. These discrepancies indicate a lack of consensus regarding the demographic groups that should be recognized and, for groups that are omitted from surveys, an inability of organizations to prioritize and evaluate R&R initiatives. Aligning inclusive demographic surveys across organizations will provide baseline data that can be used to target and evaluate R&R initiatives to better serve underrepresented groups throughout STEM. Methods We surveyed 164 STEM organizations (73 responses, rate = 44.5%) between December 2020 and July 2021 with the goal of understanding what demographic data each organization collects from its constituents (i.e., members and conference-attendees) and how the data are used. Organizations were sourced from a list of professional societies affiliated with the American Association for the Advancement of Science, AAAS, (n = 156) or from social media (n = 8). The survey was sent to the elected leadership and management firms for each organization, and follow-up reminders were sent after one month. The responding organizations represented a wide range of fields: 31 life science organizations (157,000 constituents), 5 mathematics organizations (93,000 constituents), 16 physical science organizations (207,000 constituents), 7 technology organizations (124,000 constituents), and 14 multi-disciplinary organizations spanning multiple branches of STEM (131,000 constituents). A list of the responding organizations is available in the Supplementary Materials. Based on the AAAS-affiliated recruitment of the organizations and the similar distribution of constituencies across STEM fields, we conclude that the responding organizations are a representative cross-section of the most prominent STEM organizations in the U.S. Each organization was asked about the demographic information they collect from their constituents, the response rates to their surveys, and how the data were used. Survey description The following questions are written as presented to the participating organizations. Question 1: What is the name of your STEM organization? Question 2: Does your organization collect demographic data from your membership and/or meeting attendees? Question 3: When was your organization’s most recent demographic survey (approximate year)? Question 4: We would like to know the categories of demographic information collected by your organization. You may answer this question by either uploading a blank copy of your organization’s survey (linked provided in online version of this survey) OR by completing a short series of questions. Question 5: On the most recent demographic survey or questionnaire, what categories of information were collected? (Please select all that apply)
Disability status Gender identity (e.g., male, female, non-binary) Marital/Family status Racial and ethnic group Religion Sex Sexual orientation Veteran status Other (please provide)
Question 6: For each of the categories selected in Question 5, what options were provided for survey participants to select? Question 7: Did the most recent demographic survey provide a statement about data privacy and confidentiality? If yes, please provide the statement. Question 8: Did the most recent demographic survey provide a statement about intended data use? If yes, please provide the statement. Question 9: Who maintains the demographic data collected by your organization? (e.g., contracted third party, organization executives) Question 10: How has your organization used members’ demographic data in the last five years? Examples: monitoring temporal changes in demographic diversity, publishing diversity data products, planning conferences, contributing to third-party researchers. Question 11: What is the size of your organization (number of members or number of attendees at recent meetings)? Question 12: What was the response rate (%) for your organization’s most recent demographic survey? *Organizations were also able to upload a copy of their demographics survey instead of responding to Questions 5-8. If so, the uploaded survey was used (by the study authors) to evaluate Questions 5-8.
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TwitterPursuant 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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Open Science in (Higher) Education – data of the February 2017 survey
This data set contains:
Full raw (anonymised) data set (completed responses) of Open Science in (Higher) Education February 2017 survey. Data are in xlsx and sav format.
Survey questionnaires with variables and settings (German original and English translation) in pdf. The English questionnaire was not used in the February 2017 survey, but only serves as translation.
Readme file (txt)
Survey structure
The survey includes 24 questions and its structure can be separated in five major themes: material used in courses (5), OER awareness, usage and development (6), collaborative tools used in courses (2), assessment and participation options (5), demographics (4). The last two questions include an open text questions about general issues on the topics and singular open education experiences, and a request on forwarding the respondent's e-mail address for further questionings. The online survey was created with Limesurvey[1]. Several questions include filters, i.e. these questions were only shown if a participants did choose a specific answer beforehand ([n/a] in Excel file, [.] In SPSS).
Demographic questions
Demographic questions asked about the current position, the discipline, birth year and gender. The classification of research disciplines was adapted to general disciplines at German higher education institutions. As we wanted to have a broad classification, we summarised several disciplines and came up with the following list, including the option "other" for respondents who do not feel confident with the proposed classification:
Natural Sciences
Arts and Humanities or Social Sciences
Economics
Law
Medicine
Computer Sciences, Engineering, Technics
Other
The current job position classification was also chosen according to common positions in Germany, including positions with a teaching responsibility at higher education institutions. Here, we also included the option "other" for respondents who do not feel confident with the proposed classification:
Professor
Special education teacher
Academic/scientific assistant or research fellow (research and teaching)
Academic staff (teaching)
Student assistant
Other
We chose to have a free text (numerical) for asking about a respondent's year of birth because we did not want to pre-classify respondents' age intervals. It leaves us options to have different analysis on answers and possible correlations to the respondents' age. Asking about the country was left out as the survey was designed for academics in Germany.
Remark on OER question
Data from earlier surveys revealed that academics suffer confusion about the proper definition of OER[2]. Some seem to understand OER as free resources, or only refer to open source software (Allen & Seaman, 2016, p. 11). Allen and Seaman (2016) decided to give a broad explanation of OER, avoiding details to not tempt the participant to claim "aware". Thus, there is a danger of having a bias when giving an explanation. We decided not to give an explanation, but keep this question simple. We assume that either someone knows about OER or not. If they had not heard of the term before, they do not probably use OER (at least not consciously) or create them.
Data collection
The target group of the survey was academics at German institutions of higher education, mainly universities and universities of applied sciences. To reach them we sent the survey to diverse institutional-intern and extern mailing lists and via personal contacts. Included lists were discipline-based lists, lists deriving from higher education and higher education didactic communities as well as lists from open science and OER communities. Additionally, personal e-mails were sent to presidents and contact persons from those communities, and Twitter was used to spread the survey.
The survey was online from Feb 6th to March 3rd 2017, e-mails were mainly sent at the beginning and around mid-term.
Data clearance
We got 360 responses, whereof Limesurvey counted 208 completes and 152 incompletes. Two responses were marked as incomplete, but after checking them turned out to be complete, and we added them to the complete responses dataset. Thus, this data set includes 210 complete responses. From those 150 incomplete responses, 58 respondents did not answer 1st question, 40 respondents discontinued after 1st question. Data shows a constant decline in response answers, we did not detect any striking survey question with a high dropout rate. We deleted incomplete responses and they are not in this data set.
Due to data privacy reasons, we deleted seven variables automatically assigned by Limesurvey: submitdate, lastpage, startlanguage, startdate, datestamp, ipaddr, refurl. We also deleted answers to question No 24 (email address).
References
Allen, E., & Seaman, J. (2016). Opening the Textbook: Educational Resources in U.S. Higher Education, 2015-16.
First results of the survey are presented in the poster:
Heck, Tamara, Blümel, Ina, Heller, Lambert, Mazarakis, Athanasios, Peters, Isabella, Scherp, Ansgar, & Weisel, Luzian. (2017). Survey: Open Science in Higher Education. Zenodo. http://doi.org/10.5281/zenodo.400561
Contact:
Open Science in (Higher) Education working group, see http://www.leibniz-science20.de/forschung/projekte/laufende-projekte/open-science-in-higher-education/.
[1] https://www.limesurvey.org
[2] The survey question about the awareness of OER gave a broad explanation, avoiding details to not tempt the participant to claim "aware".
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TwitterThe National Health and Nutrition Examination Surveys (NHANES) is a program of studies designed to assess the health and nutritional status of adults and children in the United States. The NHANES combines personal interviews and physical examinations, which focus on different population groups or health topics. These surveys have been conducted by the National Center for Health Statistics (NCHS) on a periodic basis from 1971 to 1994. In 1999, the NHANES became a continuous program with a changing focus on a variety of health and nutrition measurements which were designed to meet current and emerging concerns. The sample for the survey is selected to represent the U.S. population of all ages. Many of the NHANES 2007-2008 questions also were asked in NHANES II 1976-1980, Hispanic HANES 1982-1984, NHANES III 1988-1994, and NHANES 1999-2006. New questions were added to the survey based on recommendations from survey collaborators, NCHS staff, and other interagency work groups. Estimates for previously undiagnosed conditions, as well as those known to and reported by survey respondents, are produced through the survey.
In the 2005-2006 wave, the NHANES includes over 100 datasets. Most have been combined into three datasets for convenience. Each starts with the Demographic dataset and includes datasets of a specific type.
1. National Health and Nutrition Examination Survey (NHANES), Demographic & Examination Data, 2005-2006 (The base of the Demographic dataset + all data from medical examinations).
2. National Health and Nutrition Examination Survey (NHANES), Demographic & Laboratory Data, 2005-2006 (The base of the Demographic dataset + all data from medical laboratories).
3. National Health and Nutrition Examination Survey (NHANES), Demographic & Questionnaire Data, 2005-2006 (The base of the Demographic dataset + all data from questionnaires)
Not all files from the 2005-2006 wave are included. This is for two reasons, both of which related to the merging variable (SEQN). For a subset of the files, SEQN is not a unique identifier for cases (i.e., some respondents have multiple cases) or SEQN is not in the file at all. The following datasets from this wave of the NHANES are not included in these three files and can be found individually from the "https://www.cdc.gov/nchs/nhanes/index.html" Target="_blank">NHANES website at the CDC:
Examination: Dietary Interview (Individual Foods -- First Day)
Examination: Dietary Interview (Individual Foods -- Second Day)
Examination: Food Frequency Questionnaire -- DietCalc Output
Examination: Physical Activity Monitor
Questionnaire: Dietary Supplement Use -- Ingredient Information
Questionnaire: Dietary Supplement Use -- Supplement Blend
Questionnaire: Dietary Supplement Use -- Supplement Information
Questionnaire: Dietary Supplement Use -- Drug Information
Questionnaire: Dietary Supplement Use -- Participants Use of Supplement
Questionnaire: Physical Activity Individual Activity File
Questionnaire: Prescription Medications
Variable SEQN is included for merging files within the waves. All data files should be sorted by SEQN.
Additional details of the design and content of each survey are available at the "https://www.cdc.gov/nchs/nhanes/index.html" Target="_blank">NHANES website.
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This data collection is comprised of responses from the March and April installments of the 2008 Current Population Survey (CPS). Both the March and April surveys used two sets of questions, the basic CPS and a separate supplement for each month.The CPS, administered monthly, is a labor force survey providing current estimates of the economic status and activities of the population of the United States. Specifically, the CPS provides estimates of total employment (both farm and nonfarm), nonfarm self-employed persons, domestics, and unpaid helpers in nonfarm family enterprises, wage and salaried employees, and estimates of total unemployment.In addition to the basic CPS questions, respondents were asked questions from the March supplement, known as the Annual Social and Economic (ASEC) supplement. The ASEC provides supplemental data on work experience, income, noncash benefits, and migration. Comprehensive work experience information was given on the employment status, occupation, and industry of persons 15 years old and older. Additional data for persons 15 years old and older are available concerning weeks worked and hours per week worked, reason not working full time, total income and income components, and place of residence on March 1, 2007. The March supplement also contains data covering nine noncash income sources: food stamps, school lunch program, employer-provided group health insurance plan, employer-provided pension plan, personal health insurance, Medicaid, Medicare, CHAMPUS or military health care, and energy assistance. Questions covering training and assistance received under welfare reform programs, such as job readiness training, child care services, or job skill training were also asked in the March supplement.The April supplement, sponsored by the Department of Health and Human Services, queried respondents on the economic situation of persons and families for the previous year. Moreover, all household members 15 years of age and older that are a biological parent of children in the household that have an absent parent were asked detailed questions about child support and alimony. Information regarding child support was collected to determine the size and distribution of the population with children affected by divorce or separation, or other relationship status change. Moreover, the data were collected to better understand the characteristics of persons requiring child support, and to help develop and maintain programs designed to assist in obtaining child support. These data highlight alimony and child support arrangements made at the time of separation or divorce, amount of payments actually received, and value and type of any property settlement.The April supplement data were matched to March supplement data for households that were in the sample in both March and April 2008. In March 2008, there were 4,522 household members eligible, of which 1,431 required imputation of child support data. When matching the March 2008 and April 2008 data sets, there were 170 eligible people on the March file that did not match to people on the April file. Child support data for these 170 people were imputed. The remaining 1,261 imputed cases were due to nonresponse to the child support questions. Demographic variables include age, sex, race, Hispanic origin, marital status, veteran status, educational attainment, occupation, and income. Data on employment and income refer to the preceding year, although other demographic data refer to the time at which the survey was administered.
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TwitterThe primary objective of the 2012 Indonesia Demographic and Health Survey (IDHS) is to provide policymakers and program managers with national- and provincial-level data on representative samples of all women age 15-49 and currently-married men age 15-54.
The 2012 IDHS was specifically designed to meet the following objectives: • Provide data on fertility, family planning, maternal and child health, adult mortality (including maternal mortality), and awareness of AIDS/STIs to program managers, policymakers, and researchers to help them evaluate and improve existing programs; • Measure trends in fertility and contraceptive prevalence rates, and analyze factors that affect such changes, such as marital status and patterns, residence, education, breastfeeding habits, and knowledge, use, and availability of contraception; • Evaluate the achievement of goals previously set by national health programs, with special focus on maternal and child health; • Assess married men’s knowledge of utilization of health services for their family’s health, as well as participation in the health care of their families; • Participate in creating an international database that allows cross-country comparisons that can be used by the program managers, policymakers, and researchers in the areas of family planning, fertility, and health in general
National coverage
Sample survey data [ssd]
Indonesia is divided into 33 provinces. Each province is subdivided into districts (regency in areas mostly rural and municipality in urban areas). Districts are subdivided into subdistricts, and each subdistrict is divided into villages. The entire village is classified as urban or rural.
The 2012 IDHS sample is aimed at providing reliable estimates of key characteristics for women age 15-49 and currently-married men age 15-54 in Indonesia as a whole, in urban and rural areas, and in each of the 33 provinces included in the survey. To achieve this objective, a total of 1,840 census blocks (CBs)-874 in urban areas and 966 in rural areas-were selected from the list of CBs in the selected primary sampling units formed during the 2010 population census.
Because the sample was designed to provide reliable indicators for each province, the number of CBs in each province was not allocated in proportion to the population of the province or its urban-rural classification. Therefore, a final weighing adjustment procedure was done to obtain estimates for all domains. A minimum of 43 CBs per province was imposed in the 2012 IDHS design.
Refer to Appendix B in the final report for details of sample design and implementation.
Face-to-face [f2f]
The 2012 IDHS used four questionnaires: the Household Questionnaire, the Woman’s Questionnaire, the Currently Married Man’s Questionnaire, and the Never-Married Man’s Questionnaire. Because of the change in survey coverage from ever-married women age 15-49 in the 2007 IDHS to all women age 15-49 in the 2012 IDHS, the Woman’s Questionnaire now has questions for never-married women age 15-24. These questions were part of the 2007 Indonesia Young Adult Reproductive Survey questionnaire.
The Household and Woman’s Questionnaires are largely based on standard DHS phase VI questionnaires (March 2011 version). The model questionnaires were adapted for use in Indonesia. Not all questions in the DHS model were adopted in the IDHS. In addition, the response categories were modified to reflect the local situation.
The Household Questionnaire was used to list all the usual members and visitors who spent the previous night in the selected households. Basic information collected on each person listed includes age, sex, education, marital status, education, and relationship to the head of the household. Information on characteristics of the housing unit, such as the source of drinking water, type of toilet facilities, construction materials used for the floor, roof, and outer walls of the house, and ownership of various durable goods were also recorded in the Household Questionnaire. These items reflect the household’s socioeconomic status and are used to calculate the household wealth index. The main purpose of the Household Questionnaire was to identify women and men who were eligible for an individual interview.
The Woman’s Questionnaire was used to collect information from all women age 15-49. These women were asked questions on the following topics: • Background characteristics (marital status, education, media exposure, etc.) • Reproductive history and fertility preferences • Knowledge and use of family planning methods • Antenatal, delivery, and postnatal care • Breastfeeding and infant and young children feeding practices • Childhood mortality • Vaccinations and childhood illnesses • Marriage and sexual activity • Fertility preferences • Woman’s work and husband’s background characteristics • Awareness and behavior regarding HIV-AIDS and other sexually transmitted infections (STIs) • Sibling mortality, including maternal mortality • Other health issues
Questions asked to never-married women age 15-24 addressed the following: • Additional background characteristics • Knowledge of the human reproduction system • Attitudes toward marriage and children • Role of family, school, the community, and exposure to mass media • Use of tobacco, alcohol, and drugs • Dating and sexual activity
The Man’s Questionnaire was administered to all currently married men age 15-54 living in every third household in the 2012 IDHS sample. This questionnaire includes much of the same information included in the Woman’s Questionnaire, but is shorter because it did not contain questions on reproductive history or maternal and child health. Instead, men were asked about their knowledge of and participation in health-careseeking practices for their children.
The questionnaire for never-married men age 15-24 includes the same questions asked to nevermarried women age 15-24.
All completed questionnaires, along with the control forms, were returned to the BPS central office in Jakarta for data processing. The questionnaires were logged and edited, and all open-ended questions were coded. Responses were entered in the computer twice for verification, and they were corrected for computeridentified errors. Data processing activities were carried out by a team of 58 data entry operators, 42 data editors, 14 secondary data editors, and 14 data entry supervisors. A computer package program called Census and Survey Processing System (CSPro), which was specifically designed to process DHS-type survey data, was used in the processing of the 2012 IDHS.
The response rates for both the household and individual interviews in the 2012 IDHS are high. A total of 46,024 households were selected in the sample, of which 44,302 were occupied. Of these households, 43,852 were successfully interviewed, yielding a household response rate of 99 percent.
Refer to Table 1.2 in the final report for more detailed summarized results of the of the 2012 IDHS fieldwork for both the household and individual interviews, by urban-rural residence.
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 2012 Indonesia Demographic and Health Survey (2012 IDHS) 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 2012 IDHS is only one of many samples that could have been selected from the same population, using the same design and identical size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling error is 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 2012 IDHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulae. The computer software used to calculate sampling errors for the 2012 IDHS is a SAS program. This program used the Taylor linearization method
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TwitterThe Bangladesh Demographic and Health Survey (BDHS) is the first of this kind of study conducted in Bangladesh. It provides rapid feedback on key demographic and programmatic indicators to monitor the strength and weaknesses of the national family planning/MCH program. The wealth of information collected through the 1993-94 BDHS will be of immense value to the policymakers and program managers in order to strengthen future program policies and strategies.
The BDHS is intended to serve as a source of population and health data for policymakers and the research community. In general, the objectives of the BDHS are to: - asses the overall demographic situation in Bangladesh, - assist in the evaluation of the population and health programs in Bangladesh, and - advance survey methodology.
More specifically, the BDHS was designed to: - provide data on the family planning and fertility behavior of the Bangladesh population to evaluate the national family planning programs, - measure changes in fertility and contraceptive prevalence and, at the same time, study the factors which affect these changes, such as marriage patterns, urban/rural residence, availability of contraception, breastfeeding patterns, and other socioeconomic factors, and - examine the basic indicators of maternal and child health in Bangladesh.
National
Sample survey data
Bangladesh is divided into five administrative divisions, 64 districts (zillas), and 489 thanas. In rural areas, thanas are divided into unions and then mauzas, an administrative land unit. Urban areas are divided into wards and then mahallas. The 1993-94 BDHS employed a nationally-representative, two-stage sample. It was selected from the Integrated Multi-Purpose Master Sample (IMPS), newly created by the Bangladesh Bureau of Statistics. The IMPS is based on 1991 census data. Each of the five divisions was stratified into three groups: 1) statistical metropolitan areas (SMAs) 2) municipalities (other urban areas), and 3) rural areas. In rural areas, the primary sampling unit was the mauza, while in urban areas, it was the mahalla. Because the primary sampling units in the IMPS were selected with probability proportional to size from the 1991 census frame, the units for the BDHS were sub-selected from the IMPS with equal probability to make the BDHS selection equivalent to selection with probability proportional to size. A total of 304 primary sampling units were selected for the BDHS (30 in SMAs, 40 in municipalities, and 234 in rural areas), out of the 372 in the IMPS. Fieldwork in three sample points was not possible, so a total of 301 points were covered in the survey.
Since one objective of the BDHS is to provide separate survey estimates for each division as well as for urban and rural areas separately, it was necessary to increase the sampling rate for Barisal Division und for municipalities relative to the other divisions, SMAs, and rural areas. Thus, the BDHS sample is not self-weighting and weighting factors have been applied to the data in this report.
After the selection of the BDHS sample points, field staffs were trained by Mitra and Associates and conducted a household listing operation in September and October 1993. A systematic sample of households was then selected from these lists, with an average "take" of 25 households in the urban clusters and 37 households in rural clusters. Every second household was identified as selected for the husband's survey, meaning that, in addition to interviewing all ever-married women age 10-49, interviewers also interviewed the husband of any woman who was successfully interviewed. It was expected that the sample would yield interviews with approximately 10,000 ever-married women age 10-49 and 4,200 of their husbands.
Note: See detailed in APPENDIX A of the survey final report.
Data collected for women 10-49, indicators calculated for women 15-49. A total of 304 primary sampling units were selected, but fieldwork in 3 sample points was not possible.
Face-to-face
Four types of questionnaires were used for the BDHS: a Household Questionnaire, a Women's Questionnaire, a Husbands' Questionnaire, and a Service Availability Questionnaire. The contents of these questionnaires were based on the DHS Model A Questionnaire, which is designed for use in countries with relatively high levels of contraceptive use. Additions and modifications to the model questionnaires were made during a series of meetings with representatives of various organizations, including the Asia Foundation, the Bangladesh Bureau of Statistics, the Cambridge Consulting Corporation, the Family Planning Association of Bangladesh, GTZ, the International Centre for Diarrhoeal Disease Research (ICDDR,B), Pathfinder International, Population Communications Services, the Population Council, the Social Marketing Company, UNFPA, UNICEF, University Research Corporation/Bangladesh, and the World Bank. The questionnaires were developed in English and then translated into and printed in Bangla.
The Household Questionnaire was used to list all the usual members and visitors of selected households. Some basic information was collected on the characteristics of each person listed, including his/her age, sex, education, and relationship to the head of the household. The main purpose of the Household Questionnaire was to identify women and men who were eligible for individual interview. In addition, information was collected about the dwelling itself, such as the source of water, type of toilet facilities, materials used to construct the house, and ownership of various consumer goods.
The Women's Questionnaire was used to collect information from ever-married women age 10-49. These women were asked questions on the following topics: - Background characteristics (age, education, religion, etc.), - Reproductive history, - Knowledge and use of family planning methods, - Antenatal and delivery care, - Breastfeeding and weaning practices, - Vaccinations and health of children under age three, - Marriage, - Fertility preferences, and - Husband's background and respondent's work.
The Husbands' Questionnaire was used to interview the husbands of a subsample of women who were interviewed. The questionnaire included many of the same questions as the Women's Questionnaire, except that it omitted the detailed birth history, as well as the sections on maternal care, breastfeeding and child health.
The Service Availability Questionnaire was used to collect information on the family planning and health services available in and near the sampled areas. It consisted of a set of three questionnaires: one to collect data on characteristics of the community, one for interviewing family welfare visitors and one for interviewing family planning field workers, whether government or non-governent supported. One set of service availability questionnaires was to be completed in each cluster (sample point).
All questionnaires for the BDHS were returned to Dhaka for data processing at Mitra and Associates. The processing operation consisted of office editing, coding of open-ended questions, data entry, and editing inconsistencies found by the computer programs. One senior staff member, 1 data processing supervisor, questionnaire administrator, 2 office editors, and 5 data entry operators were responsible for the data processing operation. The data were processed on five microcomputers. The DHS data entry and editing programs were written in ISSA (Integrated System for Survey Analysis). Data processing commenced in early February and was completed by late April 1994.
A total of 9,681 households were selected for the sample, of which 9,174 were successfully interviewed. The shortfall is primarily due to dwellings that were vacant, or in which the inhabitants had left for an extended period at the time they were visited by the interviewing teams. Of the 9,255 households that were occupied, 99 percent were successfully interviewed. In these households, 9,900 women were identified as eligible for the individual interview and interviews were completed for 9,640 or 97 percent of these. In one-half of the households that were selected for inclusion in the husbands' survey, 3,874 eligible husbands were identified, of which 3,284 or 85 percent were interviewed.
The principal reason for non-response among eligible women and men was failure to find them at home despite repeated visits to the household. The refusal rate was very low (less than one-tenth of one percent among women and husbands). Since the main reason for interviewing husbands was to match the information with that from their wives, survey procedures called for interviewers not to interview husbands of women who were not interviewed. Such cases account for about one-third of the non-response among husbands. Where husbands and wives were both interviewed, they were interviewed simultaneously but separately.
Note: See summarized response rates by residence (urban/rural) in Table 1.1 of the survey final report.
The estimates from a sample survey are affected by two types of errors: non-sampling errors and sampling errors. Non-sampling 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
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TwitterThe 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 Dynata. Gallup chooses landline respondents at random within each household based on which member had the next birthday. As of June 2023, each sample of national adults includes a minimum quota of 80% cellphone respondents and 20% 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 (conducted periodically between 2001 and 2021) were significantly larger because Gallup oversampled Black and Hispanic adults 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.
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N = 275 as patients were allowed to choose whether to answer this question.†N = 12 as patients were allowed to choose whether to answer this question.–Blank indicates that this question was not asked of that survey group.§Based on N = 63 who responded they were not able to follow the recommendation.‡Trade name for oseltamivir. Trade name was chosen as this was likely more recognizable to survey participants.*Based on N = 62 for the completed group and N = 2 for the did not complete group who were advised to take oseltamivir (Tamiflu).
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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.
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TwitterThe Survey Assessment of Vietnamese Youth (SAVY) undertaken in late 2003 was a collaboration of the Ministry of Health, General Statistics Office with technical and financial support from the World Health Organization (WHO) and the United Nations Children’s Fund (UNICEF).
This is the first nationwide baseline survey of youth ever undertaken in Viet Nam. It mainly aims to collect data on various aspects of youth life in order to inform policy and programmes in the adolescent and youth health and development area.
SAVY reveals a positive picture of Vietnamese youth as they face both challenges and opportunities in a changing economic and social environment. Compared with young people in other Asian countries, Vietnamese youth display relatively less risky behaviour, are supported by protective factors and are optimistic and eager to build a prosperous country. However, this survey does reveal that some young people will encounter considerable challenges in their transition to adulthood, unless provided with support. It is important that parents, the community and the government, with the support of international agencies and young people, work together to ensure the healthy development of young people in Viet Nam.
The survey involved 7,584 youth aged 14-25 years from 42 provinces across the country, from the smallest rural hamlet to the largest cities. Using a household sample, youth were invited to a central location to complete both a face-to-face interview and a self-administered anonymous survey which contained sensitive questions young people could answer in private. What results is the most extensive understanding of the social life, attitudes and aspirations of young Vietnamese people today.
Survey Objectives - Provide information that can best inform future initiatives to promote the healthy development of youth across the country; - Inform policy and program development in the Adolescent and Youth Health area in the immediate future; and - Provide baseline data about Vietnamese youth to identify trends and patterns in the coming years.
Survey Content The questionnaire was designed through a very dynamic process, where experience from previous surveys was examined and opinion of young people ware actively solicited to ensure quality and relevance. The specific information collected through the questionnaire includes: Personal demographics Schooling, education Vocational training, Work and employment Puberty: knowledge and behaviors about reproductive health Dating and friendships HIV/AIDS Injury, illness and physical health Attitudes, perceptions and behaviors Social factors and emotional wellbeing Mass media Future aspirations
Survey Implementation SAVY is a collaborative effort between many agencies and young people. It is the result of extensive investment and parnership building between the Vietnamese Government through the Ministry of Health, the General Statistics Office, and United Nations agencies, notably The World Health Organisation and the United Nations Children's Fund. Several other organizations, from a variety of sectors, also contributed to the endeavor, notably the Ministry of Education and Training (MoET), the Central Youth Union (YU) and the Vietnam Women's Union (VWU). In order to ensure that the survey was methodologically sound, the East- West Centrer (Honolulu, Hawaii) provided intensive technical assisstance.
Survey Results Results from the surveys, including national reports, and micro level datasets. The dataset was formatted by *.sav (SPSS) and *.dta (STATA) More information and electronic files of SAVY, visit : http://www.moh.gov.vn/SKSS/Savy_htm/savy.htm
National
Youth aged 14-25 years
The survey covered all youths aged 14-25 years resident in the household. The SAVY sample did not include Vietnamese youth not living with their families nor those living in military barracks, social protection centers, dormitories, re-education centers and drug treatment centers.
Sample survey data [ssd]
The SAVY sample is a national representative sample of youth (persons ages 14-25 years) living in households across the eight economic regions of Viet Nam. THe sample was drawn from the sub-sample of 45,000 households in the 2002 Viet Nam Living Standards Survey (VLSS 2002), within a multi-staged and stratified design. The youth in the SAVY sample design are sufficient to represent the nation as a whole, as well as the urban and rural separely. The largest cities (Hanoi and Ho Chi Minh) were over sampled in order to provide for increased statistical power in that segment of the total population of youth.
Forty-two out of 61 provinces were selected for the SAVY sample, using the probability proportional to size (PPS) method to maintain representativeness . At the next stage of sampling, enumeration areas (EAs) in each province were selected. In those EAs sampled, all youth aged 14 through 25 were identified (i.e, those born between 1978 and 1989) males and females, married and non married from the 20 households that had been selected for the VLSS2002. The youth cohort represents all youth, but not those living in special arrangements, such as barracks, re-education centers, social protection centers, factories and dormitories.
The 61 provinces in the VLSS 2002 sample included 2.250 EAS, and the 42 provinces selected for SAVY included 1643 EAs. From these, a total of 446 EAs were selected for the SAVY sample. These EAs contained 8920 households corresponding to a population of 40,140 (about 4.5 persons per household). Since youth aged 14-25 account for 24.5% of the total population (the figure in the 1999 census), the anticipated number of youth in the SAVY sample was approximately 9,835. If the mobilization rate (percentage of eligible youth actually interviewed) was 90% then the number of youth interviewed woul be estimated to be about 8,850. In the actual SAVY field experiece, the mobilization rate was 85% and the number of completed interviews was 7,584.
The sample is therefore representative, and provides sufficient cases for analysis at the national level within urban and rural sectors at the national level, by gender at the nation level, and for each of the regions. Further detail on the sampling methodology is provided in the Appendix of the Final Report.
Face-to-face [f2f]
The questionnaire was designed through a very dynamic process, where experience from previous surveys was examined and opinions of young people were actively solicited to ensure quality and relevance. This process also helped to define the methodology and implications for fieldwork planning.
A number of stakeholders’ agencies, including research institutes, were involved in the development of the questionnaire. This process ensured broad participation and ownership of the questionnaire and the survey.
The questionnaire design took place in two stages. In the first stage, experienced researchers, and others interested in the survey as stakeholders, were convened to a workshop by the MoH. Potential topics, and the possible phrasing of questions using the questionnaire bank from previous studies in the region as reference, were fully discussed. Since some of the topics were deemed to be more sensitive than others, it was recommended that the questionnaire should be organized into two parts, one for an interview and the other for self-completion. On the basis of that workshop, a draft questionnaire was created for review by the workshop members and numerous others in stakeholder agencies, as well as by young people through a series of consultations.
Eight focus group discussions were conducted in Hanoi and HCMC, with around 60 young people of different ages in the 14-25 range who were either married or unmarried and either attending or not attending school. Participants gave detailed feedback about the terminology, the ways in which questions were posed and the sequencing of the questions, as well as which specific questions or issues they would prefer to respond to on their own, rather than with an interviewer. This process resulted in the rephrasing of a number of questions and changes to the self-completed section.
Preliminary training was conducted for field-testing of the questionnaire. Participants came from the GSO Office in Tuyen Quang, Hue and HCMC, representing the north, south and central regions of Viet Nam. A group of 50 young males and females, either married or unmarried and either attending or not attending school, participated in the interviewers’ practice session. In the debriefing discussions, these young people expressed their feelings about the interviews, the questions asked, what they liked and did not like about the process, seating arrangements, ideas of what topics/issues they thought might still be missing in the draft questionnaire, and what they thought would be needed to make good interviewers. Field testing with around 180 young people from six communes in these three provinces then took place.
The second stage involved further vetting of questionnaire sections and was coordinated by the GSO. The review meeting following the field trips recommended the need for another field testing exercise, particularly because little experience had been gained from testing with urban young people and interviewing ethnic minority young people through interpreters. Following the second round of field-testing in Hanoi and Yen Bai, the feedback was incorporated to finalise the questionnaire for the interviewers training. At the training, further revision and refinement of
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TwitterThe 1993 Ghana Demographic and Health Survey (GDHS) is a nationally representative survey of 4,562 women age 15-49 and 1,302 men age 15-59. The survey is designed to furnish policymakers, planners and program managers with factual, reliable and up-to-date information on fertility, family planning and the status of maternal and child health care in the country. The survey, which was carried out by the Ghana Statistical Service (GSS), marks Ghana's second participation in the worldwide Demographic and Health Surveys (DHS) program.
The principal objective of the 1993 GDHS is to generate reliable and current information on fertility, mortality, contraception and maternal and child health indicators. Such data are necessary for effective policy formulation as well as program design, monitoring and evaluation. The 1993 GDHS is, in large measure, an update to the 1988 GDHS. Together, the two surveys provide comparable information for two points in time, thus allowing assessment of changes and trends in various demographic and health indicators over time.
Long-term objectives of the survey include (i) strengthening the capacity of the Ghana Statistical Service to plan, conduct, process and analyze data from a complex, large-scale survey such as the Demographic and Health Survey, and (ii) contributing to the ever-expanding international database on demographic and health-related variables.
National
Sample survey data
The 1993 GDHS is a stratified, self-weighting, nationally representative sample of households chosen from 400 Enumeration Areas (EAs). The 1984 Population Census EAs constituted the sampling frame. The frame was first stratified into three ecological zones, namely coastal, forest and savannah, and then into urban and rural EAs. The EAs were selected with probability proportional to the number of households. Households within selected EAs were subsequently listed and a systematic sample of households was selected for the survey. The survey was designed to yield a sample of 5,400 women age 15-49 and a sub-sample of males age 15-59 systematically selected from one-third of the 400 EAs.
Note: See detailed description of sample design in APPENDIX A of the survey report.
Face-to-face
Survey instruments used to elicit information for the 1993 GDHS are 1) Household Schedule 2) Women's Questionnaire and 3) Men's Questionnaire.
The questionnaires were structured based on the Demographic and Health Survey Model B Questionnaire designed for countries with low levels of contraceptive use. The final version of the questionnaires evolved out of a series of meetings with personnel of relevant ministries, institutions and organizations engaged in activities relating to fertility and family planning, health and nutrition and rehabilitation of persons with disabilities.
The questionnaires were first developed in English and later translated and printed in five major local languages, namely: Akan, Dagbani, Ewe, Ga, and Hausa. In the selected households, all usual members and visitors were listed in the household schedule. Background information, such as age, sex, relationship to head of household, marital status and level of education, was collected on each listed person. Questions on economic activity, occupation, industry, employment status, number of days worked in the past week and number of hours worked per day was asked of all persons age seven years and over. Those who did not work during the reference period were asked whether or not they actively looked for work.
Information on the health and disability status of all persons was also collected in the household schedule. Migration history was elicited from all persons age 15 years and over, as well as information on the survival status and residence of natural parents of all children less than 15 years in the household.
Data on source of water supply, type of toilet facility, number of sleeping rooms available to the household, material of floor and ownership of specified durable consumer goods were also elicited.
Finally, the household schedule was the instrument used to identify eligible women and men from whom detailed information was collected during the individual interview.
The women's questionnaire was used to collect information on eligible women identified in the household schedule. Eligible women were defined as those age 15-49 years who are usual members of the household and visitors who spent the night before the interview with the household. Questions asked in the questionnaire were on the following topics:
All female respondents with at least one live birth since January 1990 and their children born since 1st January 1990 had their height and weight taken.
The men's questionnaire was administered to men in sample households in a third of selected EAs. An eligible man was 15-59 years old who is either a usual household member or a visitor who spent the night preceding the day of interview with the household.
Topics enquired about in the men's questionnaire included the following: - Background Characteristics - Reproductive History - Contraceptive Knowledge and Use - Marriage - Fertility Preferences - Knowledge of AIDS and Other STDs.
Questionnaires from the field were sent to the secretariat at the Head Office for checking and office editing. The office editing, which was undertaken by two officers, involved correcting inconsistencies in the questionnaire responses and coding open-ended questions. The questionnaires were then forwarded to the data processing unit for data entry. Data capture and verification were undertaken by four data entry operators. Nearly 20 percent of the questionnaires were verified. This phase of the survey covered four and a half months - that is, from mid-October, 1993 to the end of February, 1994.
After the data entry, three professional staff members performed the secondary editing of questionnaires that were flagged either because entries were inconsistent or values of specific variables were out of range or missing. The secondary editing was completed on 17th March, 1994 and the tables for the preliminary report were generated on 18th March, 1994. The software package used for the data processing was the Integrated System for Survey Analysis (ISSA).
A sample of 6,161 households was selected, from which 5,919 households were contacted for interview. Interviews were successfully completed in 5,822 households, indicating a household response rate of 98 percent. About 3 percent of selected households were absent during the interviewing period, and are excluded from the calculations of the response rate.
Even though the sample was designed to yield interviews with nearly 5,400 women age 15-49 only 4,700 women were identified as eligible for the individual interview. Individual interviews were successfully completed for 4,562 eligible women, giving a response rate of 97 percent. Similarly, instead of the expected 1,700 eligible men being identified in the households only 1,354 eligible men were found and 1,302 of these were successfully interviewed, with a response rate of 96 percent.
The principal reason for non-response among eligible women and men was not finding them at home despite repeated visits to the households. However, refusal rates for both eligible women and men were low, 0.3 percent and 0.2 percent, respectively.
Note: See summarized response rates in Table 1.1 of the survey report.
The results from sample surveys are affected by two types of errors, non-sampling error and sampling error. Non-sampling error is due to mistakes made in carrying out field activities, such as failure to locate and interview the correct household, errors in the way the questions are asked, misunderstanding on the part of either the interviewer or the respondent, data entry errors, etc. Although efforts were made during the design and implementation of the 1993 GDHS to minimize this type of error, non-sampling errors are impossible to avoid and difficult to evaluate statistically.
Sampling errors, on the other hand, can be measured statistically. The sample of eligible women selected in the 1993 GDHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each one would have yielded results that differed somewhat from the actual sample selected. The sampling error is a measure of the variability between all possible samples; although it is not known exactly, it can be estimated from the survey results.
Sampling error is usually measured in terms of standard error of a particular statistic (mean, percentage, etc.), which is the square root of the variance of the statistic. The standard error can be used to calculate confidence intervals within which, apart from non-sampling errors, 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 same statistic as measured in 95 percent of all possible samples with the same design (and expected size) will fall within a range
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TwitterThe National Health and Nutrition Examination Surveys (NHANES) is a program of studies designed to assess the health and nutritional status of adults and children in the United States. The NHANES combines personal interviews and physical examinations, which focus on different population groups or health topics. These surveys have been conducted by the National Center for Health Statistics (NCHS) on a periodic basis from 1971 to 1994. In 1999, the NHANES became a continuous program with a changing focus on a variety of health and nutrition measurements which were designed to meet current and emerging concerns. The sample for the survey is selected to represent the U.S. population of all ages. Many of the NHANES 2007-2008 questions also were asked in NHANES II 1976-1980, Hispanic HANES 1982-1984, NHANES III 1988-1994, and NHANES 1999-2006. New questions were added to the survey based on recommendations from survey collaborators, NCHS staff, and other interagency work groups. Estimates for previously undiagnosed conditions, as well as those known to and reported by survey respondents, are produced through the survey.
In the 2005-2006 wave, the NHANES includes over 100 datasets. Most have been combined into three datasets for convenience. Each starts with the Demographic dataset and includes datasets of a specific type.
1. National Health and Nutrition Examination Survey (NHANES), Demographic & Examination Data, 2005-2006 (The base of the Demographic dataset + all data from medical examinations).
2. National Health and Nutrition Examination Survey (NHANES), Demographic & Laboratory Data, 2005-2006 (The base of the Demographic dataset + all data from medical laboratories).
3. National Health and Nutrition Examination Survey (NHANES), Demographic & Questionnaire Data, 2005-2006 (The base of the Demographic dataset + all data from questionnaires)
Not all files from the 2005-2006 wave are included. This is for two reasons, both of which related to the merging variable (SEQN). For a subset of the files, SEQN is not a unique identifier for cases (i.e., some respondents have multiple cases) or SEQN is not in the file at all. The following datasets from this wave of the NHANES are not included in these three files and can be found individually from the "https://www.cdc.gov/nchs/nhanes/index.html" Target="_blank">NHANES website at the CDC:
Examination: Dietary Interview (Individual Foods -- First Day)
Examination: Dietary Interview (Individual Foods -- Second Day)
Examination: Food Frequency Questionnaire -- DietCalc Output
Examination: Physical Activity Monitor
Questionnaire: Dietary Supplement Use -- Ingredient Information
Questionnaire: Dietary Supplement Use -- Supplement Blend
Questionnaire: Dietary Supplement Use -- Supplement Information
Questionnaire: Dietary Supplement Use -- Drug Information
Questionnaire: Dietary Supplement Use -- Participants Use of Supplement
Questionnaire: Physical Activity Individual Activity File
Questionnaire: Prescription Medications
Variable SEQN is included for merging files within the waves. All data files should be sorted by SEQN.
Additional details of the design and content of each survey are available at the "https://www.cdc.gov/nchs/nhanes/index.html" Target="_blank">NHANES website.
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Description
The research employed a mixed methods online survey to understand better the meaning, use, and development of academic research software at the University of Illinois Urbana-Champaign. Other objectives include understanding academic research software support and training needs to make projects successful at Illinois, as well as investigating the use of generative AI tools in using and creating research software.
At the beginning of the survey, all participants gave informed consent. The University of Illinois Urbana-Champaign Institutional Review Board (IRB Protocol no.: Project IRB24-0989) reviewed the study and gave it an exempt determination.
Data collection took place from August 2024 to October 2024. Prior to data analysis, identifiable respondent details were removed during the data cleaning process. Not Applicable and Unsure style responses were used for descriptive statistics, but these responses were excluded for inferential statistics.
Survey design
At the beginning of the online survey, a consent form was provided based on guidelines from the University of Illinois Institutional Review Board to the respondents stating the aims of the study, its benefits and risks, ethical guidelines, being a voluntary survey for participation and withdrawal, privacy and confidentiality, data security, estimated time for survey completion, and contact information of researchers for asking questions. Respondents clicked to indicate their consent. Survey questions were divided into four parts: demographic information, using software for research, creating software for research, and the protocol of citing software for research. The survey had to stop points, whereby not all questions applied to respondents, which led to different sample sizes at the stop points. At the opening of the survey, the number of respondents was 251 with the funding demographic question being answered by all respondents, while other demographic questions had between 225 and 228 respondents answering them. For the first stop question, using research software in their research, the total respondents was 212, and at the last stop question, respondents considering themselves to be research developers, the total number of respondents was 74. The last question of the survey was answered by 71 respondents. Respondents may also have left the survey for other reasons. The questions were primarily closed-type questions with single choice, multiple choice, or Likert scale, as well as a few open-ended questions. Likert scale responses were created utilizing validated scales from Vagias' (2006) Likert Type Scale Response Anchors.
Sampling
Survey Respondents’ Demographics
While most respondents were Tenure Track Faculty (34.7%, f=227), other key categories included Principal Investigator (22.4%, f=227) and Research Scientist (12.1%, f=227). Computer Science, Information Science, Mathematics, and Engineering fields combined for 16% (f=228) of the respondents surveyed, but it should be noted the remaining respondents were from various academic fields across campus from various arts, humanities, and social science fields (25%, f=228) to agriculture (10%, f=228), education (5%, f=228), economics (3%, f=228), medical sciences (4%, f=228), and politics and policy/law (1%, f=228). Most respondents were likely to receive funding from various government agencies. A more detailed breakdown of the demographic information can be found in the supplemental figures. Of the 74 respondents who answered whether they were a research software developer, most respondents did not consider themselves a research software developer, with respondents stating Not at All (39%, n=74) and Slightly (22%, n=74). In addition, open-ended questions asked for further detail about research software titles used in research, research software developer challenges, how generative AI assisted in creating research software, and how research software is preserved (e.g., reproducibility).
Table 1: Survey Respondents’ Demographics
Characteristics
Respondent (%)
Age
18-24
25-34
35-44
45-54
55-64
Over 64
Preferred Not Answer
3%
14%
33%
27%
14%
7%
2%
Gender
Woman
Man
Non-binary / non-conforming
Prefer not to answer
49%
44%
2%
4%
Race
Asian
Black or African American
Hispanic or Latino
Middle Eastern or North African (MENA; new)
White
Prefer not to answer
Other
12%
5%
6%
1%
67%
8%
1%
Highest Degree
Bachelors
Masters
Professional degree (e.g., J.D.)
Doctorate
6%
19%
5%
70%
Professional Title
Tenure Track Faculty
Principal Investigator
Research Scientist
Staff
Research Faculty
Other
Teaching Faculty
Postdoc
Research Assistant
Research Software Engineer
35%
22%
12%
8%
7%
4%
4%
4%
2%
2%
Academic Field
Biological Sciences
Other
Agriculture
Engineering
Psychology
Earth Sciences
Physical Sciences
Education
Medical & Health Sciences
Computer Science
Library
Chemical Sciences
Human Society
Economics
Information Science
Environment
Veterinary
Mathematical Sciences
History
Architecture
Politics and Policy
Law
18%
10%
10%
9%
8%
6%
6%
5%
4%3%
3%
3%
3%
3%
2%
2%
2%
2%
1%
1%
1%
0%
Years Since Last Degree
Less than 1 Year
1-2 Years
3-5 Years
6-9 Years
10-15 Years
More than 15 Years
4%
8%
11%
14%
24%
40%
Receive Funding
Yes
No
73%
27%
Funders for Research
Other
National Science Foundation (NSF)
United States Department of Agriculture (USDA)
National Institute of Health (NIH)
Department of Energy (DOE)
Department of Defense (DOD)
Environmental Protection Agency (EPA)
National Aeronautics and Space Administration (NASA)
Bill and Melinda Gates Foundation
Advanced Research Projects Agency - Energy (ARPA-E)
Institute of Education Sciences
Alfred P. Sloan Foundation
W.M. Keck Foundation
Simons Foundation
Gordon and Betty Moore Foundation
Department of Justice (DOJ)
National Endowment for the Humanities (NEH)
Congressionally Directed Medical Research Programs (CDMRP)
Andrew W. Mellon Foundation
22%
18%
18%
11%
9%
5%
4%
4%
2%
2%
1%
1%
1%
1%
1%
1%
0%
0%
0%
Table 2: Survey Codebook
QuestionID
Variable
Variable Label
Survey Item
Response Options
1
age
Respondent’s Age
Section Header:
Demographics Thank you for your participation in this survey today! Before you begin to answer questions about academic research software, please answer a few demographic questions to better contextualize your responses to other survey questions.
What is your age?
Select one choice.
Years
1-Under 18
2-18-24
3-25-34
4-35-44
5-45-54
6-55-64
7-Over 64
8-Prefer not to answer
2
gender
Respondent’s Gender
What is your gender?
Select one choice.
1-Female
2-Male
3-Transgender
4-Non-binary / non-conforming
5-Prefer not to answer
6-Other:
3
race
Respondent’s Race
What is your race?
Select one choice.
1-American Indian or Alaska Native
2-Asian
3-Black or African American
4-Hispanic or Latino
5-Middle Eastern or North African (MENA; new)
6-Native Hawaiian or Pacific Islander
7-White
8-Prefer not to answer
9-Other:
4
highest_degree
Respondent’s Highest Degree
What is the highest degree you have completed?
Select one choice.
1-None
2-High school
3-Associate
4-Bachelor's
5-Master's
6-Professional degree (e.g., J.D.)
7-Doctorate
8-Other:
5
professional_title
Respondent’s Professional Title
What is your professional title?
Select all that apply.
1-professional_title_1
Principal Investigator
2-professional_title_2
Tenure Track Faculty
3-professional_title_3
Teaching Faculty
4-professional_title_4
Research Faculty
5-professional_title_5
Research Scientist
6-professional_title_6
Research Software Engineer
7-professional_title_7
Staff
8-professional_title_8
Postdoc
9-professional_title_9
Research Assistant
10-professional_title_10
Other:
6
academic_field
Respondent’s most strongly identified Academic Field
What is the academic field or discipline you most strongly identify with (e.g., Psychology, Computer Science)?
Select one choice.
1-Chemical sciences
2-Biological sciences
3-Medical & health sciences
4-Physical sciences
5-Mathematical sciences
6-Earth sciences
7-Agriculture
8-Veterinary
9-Environment
10-Psychology
11-Law
12-Philosophy
13-Economics
14-Human society
15-Journalism
16-Library
17-Education
18-Art & Design Management
19-Engineering
20-Language
21-History
22-Politics and policy
23-Architecture
24-Computer Science
25-Information science
26-Other:
7
years_since_last_degree
Number of years since last respondent’s last degree
How many years since the award of your last completed degree?
Select one choice.
1-Less than 1 year
2-1-2 years
3-3-5 years
4-6-9 years
5-10-15 years
6-More than 15 years
8
receive_funding_for_research
Whether respondent received funding for research
Do you receive funding for your research?
1-Yes
0-No
9
funders_for_research
Respondent’s funding sources if they answered yes in Question 8
Who funds your research or work (e.g., NIH, Gates Foundation)?
Select all that apply.
1-funders_for_research_1
United States Department of Agriculture (USDA)
2-funders_for_research_2
Department of Energy (DOE)
3-funders_for_research_3
National Science
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TwitterThe 2013 Nigeria Demographic and Health Survey (NDHS) was designed to provide data to monitor the population and health situation in Nigeria with an explicit goal of providing reliable information about maternal and child health and family planning services. The primary objective of the 2013 NDHS was to provide up-to-date information on fertility levels, marriage, fertility preferences, awareness and use of family planning methods, child feeding practices, nutritional status of women and children, adult and childhood mortality, awareness and attitudes regarding HIV/AIDS, and domestic violence. This information is intended to assist policymakers and programme managers in evaluating and designing programmes and strategies for improving health and family planning services in the country.
National coverage
Sample survey data [ssd]
Sample Design The sample for the 2013 NDHS was nationally representative and covered the entire population residing in non-institutional dwelling units in the country. The survey used as a sampling frame the list of enumeration areas (EAs) prepared for the 2006 Population Census of the Federal Republic of Nigeria, provided by the National Population Commission. The sample was designed to provide population and health indicator estimates at the national, zonal, and state levels. The sample design allowed for specific indicators to be calculated for each of the six zones, 36 states, and the Federal Capital Territory, Abuja.
Administratively, Nigeria is divided into states. Each state is subdivided into local government areas (LGAs), and each LGA is divided into localities. In addition to these administrative units, during the 2006 population census, each locality was subdivided into census enumeration areas. The primary sampling unit (PSU), referred to as a cluster in the 2013 NDHS, is defined on the basis of EAs from the 2006 EA census frame. The 2013 NDHS sample was selected using a stratified three-stage cluster design consisting of 904 clusters, 372 in urban areas and 532 in rural areas. A representative sample of 40,680 households was selected for the survey, with a minimum target of 943 completed interviews per state.
A complete listing of households and a mapping exercise were carried out for each cluster from December 2012 to January 2013, with the resulting lists of households serving as the sampling frame for the selection of households. All regular households were listed. The NPC listing enumerators were trained to use Global Positioning System (GPS) receivers to calculate the coordinates of the 2013 NDHS sample clusters.
A fixed sample take of 45 households were selected per cluster. All women age 15-49 who were either permanent residents of the households in the 2013 NDHS sample or visitors present in the households on the night before the survey were eligible to be interviewed. In a subsample of half of the households, all men age 15-49 who were either permanent residents of the households in the sample or visitors present in the households on the night before the survey were eligible to be interviewed. Also, a subsample of one eligible woman in each household was randomly selected to be asked additional questions regarding domestic violence.
For further details on sample size and design, see Appendix B of the final report.
Face-to-face [f2f]
Three questionnaires were used in the 2013 NDHS: the Household Questionnaire, the Woman’s Questionnaire, and the Man’s Questionnaire.
The Household Questionnaire was used to list all of the usual members of and visitors to the selected households. Some basic information was collected on the characteristics of each person listed, including age, sex, marital status, education, and relationship to the head of the household. Information on other characteristics of household members was collected as well, including current school attendance and survivorship of parents among those under age 18. If a child in the household had a parent who was sick for more than three consecutive months in the 12 months preceding the survey or a parent who had died, additional questions related to support for orphans and vulnerable children were asked. Furthermore, if an adult in the household was sick for more than three consecutive months in the 12 months preceding the survey or an adult in the household had died, questions were asked relating to support for sick people or people in households where a member had died.
The Household Questionnaire also collected information on characteristics of the household’s dwelling unit, such as source of water; type of toilet facilities; materials used for the floor of the house; ownership of various durable goods; ownership of agricultural land; ownership of livestock, farm animals, or poultry; and ownership and use of mosquito nets and long-lasting insecticidal nets. The Household Questionnaire was further used to record height and weight measurements for children age 0-59 months and women age 15-49. In addition, data on the age and sex of household members in the Household Questionnaire were used to identify women and men who were eligible for individual interviews.
The Woman’s Questionnaire was used to collect information from all women age 15-49. These women were asked questions on the following main topics: • Background characteristics (age, religion, education, literacy, media exposure, etc.) • Reproductive history and childhood mortality • Knowledge, source, and use of family planning methods • Fertility preferences • Antenatal, delivery, and postnatal care • Breastfeeding and infant feeding practices • Child immunisation and childhood illnesses • Marriage and sexual activity • Women’s work and husbands’ background characteristics • Malaria prevention and treatment • Women’s decision making • Awareness of AIDS and other sexually transmitted infections • Maternal mortality • Domestic violence
The Man’s Questionnaire was administered to all men age 15-49 in every second household in the 2013 NDHS sample. The Man’s Questionnaire collected much of the same information found in the Woman’s Questionnaire but was shorter because it did not contain a detailed reproductive history or questions on maternal and child health or nutrition.
The processing of the 2013 NDHS data began simultaneously with the fieldwork. Completed questionnaires were edited in the field immediately by the field editors and checked by the supervisors before being dispatched to the data processing centre in Abuja. The questionnaires were then edited and entered by 26 data processing personnel specially trained for this task. Data were entered using the CSPro computer package, and all data were entered twice to allow 100 percent verification. The concurrent processing of the data offered a distinct advantage because of the assurance that the data were error free and authentic. Moreover, the double entry of data enabled easy comparisons and identification of errors and inconsistencies. Inconsistencies were resolved by tallying results with the paper questionnaire entries. Secondary editing of the data was completed in the last week of July 2013. The final cleaning of the data set was carried out by the ICF data processing specialist and completed in August.
A total of 40,320 households were selected from 896 sample points, of which 38,904 were found to be occupied at the time of the fieldwork. Of the occupied households, 38,522 were successfully interviewed, yielding a household response rate of 99 percent. In view of the security challenges in the country, this response rate is highly encouraging and appears to be the result of a well-coordinated team effort.
In the interviewed households, a total of 39,902 women age 15-49 were identified as eligible for individual interviews, and 98 percent of them were successfully interviewed. Among men, 18,229 were identified as eligible for interviews, and 95 percent were successfully interviewed. As expected, response rates were slightly lower in urban areas than in rural areas.
Note: See summarized response rates by residence (urban/rural) in Table 1.2 of the survey report.
The estimates from a sample survey are affected by two types of errors: non-sampling errors and sampling errors. Non-sampling 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 2013 Nigeria DHS (NDHS) to minimize this type of error, non-sampling 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 2013 NDHS 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.
Sampling error is usually measured in terms of the standard error
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TwitterThe National Health and Nutrition Examination Surveys (NHANES) is a program of studies designed to assess the health and nutritional status of adults and children in the United States. The NHANES combines personal interviews and physical examinations, which focus on different population groups or health topics. These surveys have been conducted by the National Center for Health Statistics (NCHS) on a periodic basis from 1971 to 1994. In 1999, the NHANES became a continuous program with a changing focus on a variety of health and nutrition measurements designed to meet current and emerging concerns. The sample for the survey is selected to represent the U.S. population of all ages. Many of the NHANES 2001-2002 questions also were asked in NHANES II 1976-1980, Hispanic HANES 1982-1984, NHANES III 1988-1994. New questions were added to the survey based on recommendations from survey collaborators, NCHS staff, and other interagency work groups.
In the 2001-2002 wave, the NHANES includes more than 100 datasets. Most have been combined into three datasets for convenience. Each starts with the demographic dataset and includes datasets of a specific type.
1. National Health and Nutrition Examination Survey (NHANES), Demographic & Examination Data, 2001-2002 (the base of the Demographic dataset + all data from medical examinations).
2. National Health and Nutrition Examination Survey (NHANES), Demographic & Laboratory Data, 2001-2002 (the base of the Demographic dataset + all data from medical laboratories).
3. National Health and Nutrition Examination Survey (NHANES), Demographic & Questionnaire Data, 2001-2002 (the base of the Demographic dataset + all data from questionnaires).
Not all files from the 2001-2002 wave are included. This is for two reasons, both of which related to the merging variable (SEQN). For a subset of the files, SEQN is not a unique identifier for cases (i.e. some respondents have multiple cases) or SEQN is not in the file at all. The following datasets from this wave of the NHANES are not included in these three files and can be found individually from the "https://www.cdc.gov/nchs/nhanes/index.html" Target="_blank">NHANES website at the CDC:
Examination: Dietary Interview (Individual Foods File)
Examination: Dual Energy X-ray Absorptiometry (DXX)
Examination: Dual Energy X-ray Absorptiometry (DXX)
Questionnaire: Analgesics Pain Relievers
Questionnaire: Dietary Supplement Use -- Ingredient Information
Questionnaire: Dietary Supplement Use -- Supplement Blend
Questionnaire: Dietary Supplement Use -- Supplement Information
Questionnaire: Drug Information
Questionnaire: Dietary Supplement Use -- Participants Use of Supplement
Questionnaire: Physical Activity Individual Activity File
Questionnaire: Prescription Medications
Variable SEQN is included for merging files within the waves. All data files should be sorted by SEQN.
Additional details of the design and content of each survey are available at the "https://www.cdc.gov/nchs/nhanes/index.html" Target="_blank">NHANES website.
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TwitterThe Bangladesh Demographic and Health Survey (BDHS) is part of the worldwide Demographic and Health Surveys program, which is designed to collect data on fertility, family planning, and maternal and child health.
The main objective of this survey is to provide policy-makers and program managers in health and family planning with detailed information on fertility and family planning, childhood mortality, maternal and child health, nutritional status of children and mothers, and awareness of HIV/AIDS. The survey consisted of two parts: a household-level survey of women and men and a community survey around the sample points from which the households were selected. Preparations for the survey started in mid-2003 and the fieldwork was carried out between January and May 2004.The urvey was conducted under the authority of the National Institute for Population Research and Training (NIPORT) of the Ministry of Health and Family Welfare. The survey was implemented by Mitra and Associates, a Bangladeshi research firm located in Dhaka. ORC Macro of Calverton, Maryland, provided technical assistance to the project as part of its international Demographic and Health Surveys program, and financial assistance was provided by the U.S. Agency for International Development (USAID)/Bangladesh.
In general, the objectives of the BDHS are to: - Assess the overall demographic situation in Bangladesh - Assist in the evaluation of the population and health programs in Bangladesh - Advance survey methodology.
More specifically, the objective of the BDHS survey is to provide up-to-date information on fertility and childhood mortality levels; nuptiality; fertility preferences; awareness, approval, and use of family planning methods; breastfeeding practices; nutrition levels; and maternal and child health. This information is intended to assist policymakers and administrators in evaluating and designing programs and strategies for improving health and family planning services in the country.
National
Sample survey data
The sample for the 2004 BDHS covered the entire population residing in private dwellings units in the country. Administratively, Bangladesh is divided into six divisions. In turn, each division is divided into zilas, and in turn each zila into upazilas. Each urban area in the upazila is divided into wards, and into mahallas within the ward; each rural area in the upazila is divided into union parishads (UP) and into mouzas within the UPs. The urban areas were stratified into three groups, i) Standard metropolitan areas, ii) Municipality areas, and iii) Other urban areas. These divisions allow the country as a whole to be easily separated into rural and urban areas.
For the 2001 census, subdivisions called enumeration areas (EAs) were created based on a convenient number of dwellings units. Because sketch maps of EAs were accessible, EAs were considered suitable to use as primary sampling units (PSUs) for the 2004 BDHS. In each division, the list of EAs constituted the sample frame for the 2004 BDHS survey.
A target number of completed interviews with eligible women for the 2004 BDHS was set at 10,000, based on information from the 1999-2000 BDHS. The 2004 BDHS sample is a stratified, a multistage cluster sample consisting of 361 PSUs, 122 in the urban area and 239 in the rural area. After the target sample was allocated to each group area according to urban and rural areas, the number of PSUs was calculated in terms of an average of 28 completed interviews of eligible women per PSU (or an average of 30 selected households per PSU).
Mitra and Associates conducted a household listing operation in all the sample points from 3 October 2003 to 15 December 2003. A systematic sample of 10,811 households was then selected from these lists. All ever-married women age 10-49 in the selected households were eligible respondents for the women's questionnaire. For the men's survey, 50 percent of the selected households were chosen through systematic sampling. Interviewers interviewed one randomly selected man, regardless of marital status, in the age group 15-54, from each of the selected households. It was expected that the sample would yield interviews with approximately 10,000 ever-married women age 10-49 and 4,400 men age 15-54.
Note: See detailed in APPENDIX A of the survey report.
Data collected for women 10-49, indicators calculated for women 15-49.
Face-to-face
The BDHS used a Household Questionnaire, a Women’s Questionnaire, a Men’s Questionnaire, and a Community Questionnaire. The contents of these questionnaires was based on MEASURE DHS+ model questionnaire. These model questionnaires were adapted for use in Bangladesh during a series of meetings with the Technical Task Force, which consisted of representatives from NIPORT, Mitra and Associates, USAID/Dhaka, ICDDR,B’s Center for Health and Population Research, Bangladesh, Pathfinder/Dhaka, and ORC Macro. Draft questionnaires were then circulated to other interested groups and were reviewed by the BDHS Technical Review Committee. The questionnaires were developed in English and then translated into and printed in Bangla. In addition, two versions of a Verbal Autopsy Questionnaire were used. One version was for neonatal deaths (0-28 days old at death) and the other was for deaths among older children (age 29 days to 5 years at death). The verbal autopsy instruments were developed using the previous two BDHS verbal autopsy surveys, the WHO verbal autopsy questionnaire, and the instrument used since 2003 in the Matlab Health and Demographic Surveillance System.
The Household Questionnaire was used to list all the usual members and visitors in the selected households. Some basic information was collected on the characteristics of each person listed, including his/her age, sex, education, and relationship to the head of the household. The main purpose of the Household Questionnaire was to identify women and men who were eligible for individual interview. In addition, information was collected about the dwelling itself, such as the source of water, type of toilet facilities, materials used to construct the house, and ownership of various consumer goods. The arsenic level of the water used by households for drinking was also tested. The Household Questionnaire was also used to record the heights and weights of all children under six years of age.
The Women’s Questionnaire was used to collect information from ever-married women age 10-49. These women were asked questions on the following topics: - Background characteristics (age, education, religion, etc.) - Reproductive history - Knowledge and use of family planning methods - Antenatal and delivery care - Breastfeeding and weaning practices - Vaccinations and health of children under age five - Marriage - Fertility preferences - Husband’s background and respondent’s work - Awareness of AIDS and other sexually transmitted diseases - Causes of deaths of children under five years of age
The Men’s Questionnaire was used to collect information from men age 15-54 whether ever married or not. The men were asked questions on the following topics: - Background characteristics (including respondent’s work) - Health and life style (illness, use of tobacco) - Marriage and sexual activity - Participation in reproductive health care - Awareness of AIDS and other sexually transmitted diseases - Attitudes on women’s decision making roles - Domestic violence
The Community Questionnaire was completed for each sample cluster and included questions about the existence of development organizations in the community and the availability and accessibility of health and family planning services.
The Verbal Autopsy Questionnaire was used for collection of open-ended information including narrative stories on the following topics: - Identification including detailed address of respondent - Informed consent - Detailed age description of deceased child - Information about caretaker or respondent of deceased child - Detailed birth and delivery information - Open-ended section allowing the respondent to provide a narrative history - Maternal history including questions on prenatal care, labor and delivery, and obstetrical complications - Information about accidental deaths - Detailed signs and symptoms preceding death - Treatment module and information on direct, underlying - Contributing causes of death from the death certificate, if available.
All questionnaires for the BDHS were periodically returned to Dhaka for data processing at Mitra and Associates. The processing of the data collected began shortly after the fieldwork commenced. The processing operation consisted of office editing, coding of open-ended questions, data entry, and editing inconsistencies found by the computer programs. The data were processed on six microcomputers working in double shifts and carried out by 10 data entry operators and two data entry supervisors. The concurrent processing of the data was an advantage since the quality control teams were able to advise field teams of problems detected during the data entry. In particular, tables were generated to check various data quality parameters. Data processing commenced on 12 January 2004 and was completed by 24 June 2004.
A total of 10,811 households were selected for the sample; 10,523 were occupied, of which 10,500 were
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TwitterThe primary objective of the 2006 DHS is to provide to the Department of Health (DOH), Department of National Planning and Monitoring (DNPM) 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, knowledge of HIV/AIDS and behavior, sexually risk behavior and information on the general household amenities. This information contributes to policy planning, monitoring, and program evaluation for development at all levels of government particularly at the national and provincial levels. The information will also be used to assess the performance of government development interventions aimed at addressing the targets set out under the MDG and MTDS. The long-term objective of the survey is to technically strengthen the capacity of the NSO in conducting and analyzing the results of future surveys.
The successful conduct and completion of this survey is a result of the combined effort of individuals and institutions particularly in their participation and cooperation in the Users Advisory Committee (UAC) and the National Steering Committee (NSC) in the different phases of the survey.
The survey was conducted by the Population and Social Statistics Division of the National Statistical Office of PNG. The 2006 DHS was jointly funded by the Government of PNG and Donor Partners through ADB while technical assistance was provided by International Consultants and NSO Philippines.
National level Regional level Urban and Rural
The survey covered all de jure household members (usual residents), all women and men aged 15-50 years resident in the household.
Sample survey data [ssd]
The primary focus of the 2006 DHS is to provide estimates of key population and health indicators at the national level. A secondary but important priority is to also provide estimates at the regional level, and for urban and rural areas respectively. The 2006 DHS employed the same survey methodology used in the 1996 DHS. The 2006 DHS sample was a two stage self-weighting systematic cluster sample of regions with the first stage being at the census unit level and the second stage at the household level. The 2000 Census frame comprised of a list of census units was used to select the sample of 10,000 households for the 2006 DHS.
A total of 667 clusters were selected from the four regions. All census units were listed in a geographic order within their districts, and districts within each province and the sample was selected accordingly through the use of appropriate sampling fraction. The distribution of households according to urban-rural sectors was as follows:
8,000 households were allocated to the rural areas of PNG. The proportional allocation was used to allocate the first 4,000 households to regions based on projected citizen household population in 2006. The other 4,000 households were allocated equally across all four regions to ensure that each region have sufficient sample for regional level analysis.
2,000 households were allocated to the urban areas of PNG using proportional allocation based on the 2006 projected urban citizen population. This allocation was to ensure that the most accurate estimates for urban areas are obtained at the national level.
All households in the selected census units were listed in a separate field operation from June to July 2006. From the list of households, 16 households were selected in the rural census units and 12 in the urban census units using systematic sampling. All women and men age 15-50 years who were either usual residents of the selected households or visitors present in the household on the night before the survey were eligible to be interviewed. Further information on the survey design is contained in Appendix A of the survey report.
Face-to-face [f2f]
Three questionnaires were used in the 2006 DHS namely; the Household Questionnaire (HHQ), the Female Individual Questionnaire (FIQ) and the Male Individual Questionnaire (MIQ). The planning and development of these questionnaires involved close consultation with the UAC members comprising of the following line departments and agencies namely; Department of Health (DOH), Department of Education (DOE), Department of National Planning and Monitoring (DNPM), National Aids Council Secretariat (NACS), Department of Agriculture and Livestock (DAL), Department of Labour and Employment (DLE), University of Papua New Guinea (UPNG), National Research Institute (NRI) and representatives from Development partners.
The HHQ was designed to collect background information for all members of the selected households. This information was used to identify eligible female and male respondents for the respective individual questionnaires. Additional information on household amenities and services, and malaria prevention was also collected.
The FIQ contains questions on respondents background, including marriage and polygyny; birth history, maternal and child health, knowledge and use of contraception, fertility preferences, HIV/AIDS including new modules on sexual risk behaviour and attitudes to issues of well being. All females age 15-50 years identified from the HHQ were eligible for interview using this questionnaire.
The MIQ collected almost the same information as in the FIQ except for birth history. All males age 15-50 years identified from the HHQ were eligible to be interviewed using the MIQ.
Two pre-tests were carried out aimed at testing the flow of the existing and new questions and the administering of the MIQ between March and April 2006. The final questionnaires contained all the modules used in the 1996 DHS including new modules on malaria prevention, sexual risk behaviour and attitudes to issues of well being.
All questionnaires from the field were sent to the NSO headquarters in Port Moresby in February 2007 for editing and coding, data entry and data cleaning. Editing was done in 3 stages to enable the creation of clean data files for each province from which the tabulations were generated. Data entry and processing were done using the CSPro software and was completed by October 2008.
Table A.2 of the survey report provides a summary of the sample implementation of the 2006 DHS. Despite the recency of the household listing, approximately 7 per cent of households could not be contacted due to prolonged absence or because their dwellings were vacant or had been destroyed. Among the households contacted, a response rate of 97 per cent was achieved. Within the 9,017 households successfully interviewed, a total of 11, 456 women and 11, 463 of men age 15-49 years were eligible to be interviewed. Successful interviews were conducted with 90 per cent of eligible women (10, 353) and 88 per cent of eligible men (10,077). The most common cause of non-response was absence (5 per cent). Among the regions, the rate of success among women was highest in all the regions (92 per cent each) except for Momase region at 86 per cent. The rate of success among men was highest in Highlands and Islands region and lowest in Momase region. The overall response rate, calculated as the product of the household and female individual response rate (.97*.90) was 87 per cent.
Appendix B of the survey report describes the general procedure in the computation of sampling errors of the sample survey estimates generated. It basically follows the procedure adopted in most Demographic and Health Surveys.
Appendix C explains to the data users the quality of the 2006 DHS. Non-sampling errors are those that occur in surveys and censuses through the following causes: a) Failure to locate the selected household b) Mistakes in the way questions were asked c) Misunderstanding by the interviewer or respondent d) Coding errors e) Data entry errors, etc.
Total eradication of non-sampling errors is impossible however great measures were taken to minimize them as much as possible. These measures included: a) Careful questionnaire design b) Pretesting of survey instruments to guarantee their functionality c) A month of interviewers’ and supervisors’ training d) Careful fieldwork supervision including field visits by NSOHQ personnel e) A swift data processing prior to data entry f ) The use of interactive data entry software to minimize errors
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TwitterThe principal objective of the Republic of the Marshall Islands 2007 Demographic and Health Survey (2007 RMIDHS) is to provide current and reliable data on fertility and family planning behavior, child mortality, adult and maternal mortality, children’s nutritional status, the utilization of maternal and child health services, and knowledge of HIV and AIDS. The specific objectives of the survey are to: • collect data at the national level that will allow the calculation of key demographic rates; • analyze the direct and indirect factors that determine the level and trends of fertility; • measure the level of contraceptive knowledge and practice among women and men by method, urban/rural residence, and region; • collect high-quality data on family health, including immunization coverage among children, prevalence and treatment of diarrhea and other diseases among children under five, and maternity care indicators (including antenatal visits, assistance at delivery, and postnatal care); • collect data on infant and child mortality; • obtain data on child feeding practices, including breastfeeding, and collect ‘observation’ information to use in assessing the nutritional status of women and children; • collect data on knowledge and attitudes of women and men about sexually transmitted infections (STIs), HIV and AIDS and evaluate patterns of recent behavior regarding condom use; and • collect data on support to mentally ill persons and information on the incidence of suicide.
This information is essential for informed policy decisions, planning, monitoring, and evaluation of programs on health in general and reproductive health in particular at both national level and in urban and rural areas. A long-term objective of the survey is to strengthen the technical capacity of government organizations to plan, conduct, process, and analyze data from complex national population and health surveys. Moreover, the 2007 RMIDHS provides national, rural, and urban estimates on population and health that are comparable to data collected in similar surveys in other Pacific DHS pilot countries and other developing countries.
National
Sample survey data [ssd]
The primary focus of the 2007 RMIDHS was to provide estimates of key population and health indicators, including fertility and mortality rates, for the country as a whole and for urban and rural areas separately. The survey used the sampling frame provided by the list of census enumeration areas, with population and household information from the 1999 RMI Census and the 2006 Community Survey.
The survey was designed to obtain completed interviews of 1,070 women aged 15-49. In addition, males aged 15-59 in every second household were interviewed. To take non-response into account, a total of 608 households countrywide were selected: 295 in urban areas and 313 in rural areas.
Face-to-face [f2f]
Three questionnaires were administered for the 2007 RMIDHS: a household questionnaire, a women’s questionnaire, and a men’s questionnaire. These were adapted to reflect population and health issues relevant to the Marshall Islands at a series of meetings with various stakeholders from government ministries and agencies, non-governmental organizations (NGOs) and international donors. The final draft of the questionnaires was discussed at a questionnaire design workshop organized by EPPSO in September 2006 in Majuro. The survey questionnaires were then translated into the local language (Marshallese) and pretested from November 16 to December 13, 2006.
The household questionnaire was used to list all the usual members and visitors in the selected households and to identify women and men who were eligible for the individual interview. Some basic information was collected on the characteristics of each person listed, including age, sex, education, and relationship to the head of the household. For children under age 18, the survival status of their parents was determined. The household questionnaire also collected information on characteristics of the household’s dwelling unit, such as the source of water, type of toilet facilities, materials used for the floor of the house, and ownership of various durable goods. Additionally, it was used to record information on mental illness and suicide experiences of members of the household.
The women’s questionnaire was used to collect information from all women aged 15–49. The women were asked questions on: • characteristics such as education, residential history, and media exposure; • pregnancy history and childhood mortality; • knowledge and use of family planning methods; • fertility preferences; • antenatal, delivery, and postnatal care; • breastfeeding and infant feeding practices; • immunization and childhood illnesses; • marriage and sexual activity; • their own work and their husband’s background characteristics; and • awareness and behavior regarding HIV and other STIs.
The men’s questionnaire was administered to all men aged 15–59 living in every second household in the 2007 RMIDHS sample. It collected much of the same information found in the women’s questionnaire, but was shorter because it did not contain a detailed reproductive history or questions on maternal and child health or nutrition.
The processing of the 2007 RMIDHS results began soon after the start of fieldwork. Completed questionnaires were returned periodically from the field to the EPPSO data processing center in Majuro, where they were entered and edited by four data processing personnel specially trained for this task. The data processing personnel were supervised by EPPSO staff. The concurrent processing of the data was an advantage since field check tables were generated early on to monitor various data quality parameters. As a result, specific and ongoing feedback was given to the field teams to improve performance. The data entry and editing of the questionnaires was completed by June 30, 2007. Data processing was done using CSPro.
A total of 1,141 households were selected for the sample, of which 1,131 were found to be occupied during data collection. Of these existing households, 1,106 were successfully interviewed, giving a household response rate of 98 percent.
In the households, 1,742 women were identified as eligible for the individual interview. Interviews were completed with 1,625 women, yielding a response rate of 93 percent. Of the 1,218 eligible men identified in the selected sub-sample of households, 87 percent were successfully interviewed. Response rates were higher in rural than urban areas, with the rural–urban difference in response rates most marked among eligible men.
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 D of the final survey report.
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TwitterThe 1991 Indonesia Demographic and Health Survey (IDHS) is a nationally representative survey of ever-married women age 15-49. It was conducted between May and July 1991. The survey was designed to provide information on levels and trends of fertility, infant and child mortality, family planning and maternal and child health. The IDHS was carried out as collaboration between the Central Bureau of Statistics, the National Family Planning Coordinating Board, and the Ministry of Health. The IDHS is follow-on to the National Indonesia Contraceptive Prevalence Survey conducted in 1987.
The DHS program has four general objectives: - To provide participating countries with data and analysis useful for informed policy choices; - To expand the international population and health database; - To advance survey methodology; and - To help develop in participating countries the technical skills and resources necessary to conduct demographic and health surveys.
In 1987 the National Indonesia Contraceptive Prevalence Survey (NICPS) was conducted in 20 of the 27 provinces in Indonesia, as part of Phase I of the DHS program. This survey did not include questions related to health since the Central Bureau of Statistics (CBS) had collected that information in the 1987 National Socioeconomic Household Survey (SUSENAS). The 1991 Indonesia Demographic and Health Survey (IDHS) was conducted in all 27 provinces of Indonesia as part of Phase II of the DHS program. The IDHS received financial assistance from several sources.
The 1991 IDHS was specifically designed to meet the following objectives: - To provide data concerning fertility, family planning, and maternal and child health that can be used by program managers, policymakers, and researchers to evaluate and improve existing programs; - To measure changes in fertility and contraceptive prevalence rates and at the same time study factors which affect the change, such as marriage patterns, urban/rural residence, education, breastfeeding habits, and the availability of contraception; - To measure the development and achievements of programs related to health policy, particularly those concerning the maternal and child health development program implemented through public health clinics in Indonesia.
National
Sample survey data [ssd]
Indonesia is divided into 27 provinces. For the implementation of its family planning program, the National Family Planning Coordinating Board (BKKBN) has divided these provinces into three regions as follows:
The 1990 Population Census of Indonesia shows that Java-Bali contains about 62 percent of the national population, while Outer Java-Bali I contains 27 percent and Outer Java-Bali II contains 11 percent. The sample for the Indonesia DHS survey was designed to produce reliable estimates of contraceptive prevalence and several other major survey variables for each of the 27 provinces and for urban and rural areas of the three regions.
In order to accomplish this goal, approximately 1500 to 2000 households were selected in each of the provinces in Java-Bali, 1000 households in each of the ten provinces in Outer Java-Bali I, and 500 households in each of the 11 provinces in Outer Java-Bali II for a total of 28,000 households. With an average of 0.8 eligible women (ever-married women age 15-49) per selected household, the 28,000 households were expected to yield approximately 23,000 individual interviews.
Note: See detailed description of sample design in APPENDIX A of the survey report.
Face-to-face [f2f]
The DHS model "A" questionnaire and manuals were modified to meet the requirements of measuring family planning and health program attainment, and were translated into Bahasa Indonesia.
The first stage of data editing was done by the field editors who checked the completed questionnaires for completeness and accuracy. Field supervisors also checked the questionnaires. They were then sent to the central office in Jakarta where they were edited again and open-ended questions were coded. The data were processed using 11 microcomputers and ISSA (Integrated System for Survey Analysis).
Data entry and editing were initiated almost immediately after the beginning of fieldwork. Simple range and skip errors were corrected at the data entry stage. Secondary machine editing of the data was initiated as soon as sufficient questionnaires had been entered. The objective of the secondary editing was to detect and correct, if possible, inconsistencies in the data. All of the data were entered and edited by September 1991. A brief report containing preliminary survey results was published in November 1991.
Of 28,141 households sampled, 27,109 were eligible to be interviewed (excluding those that were absent, vacant, or destroyed), and of these, 26,858 or 99 percent of eligible households were successfully interviewed. In the interviewed households, 23,470 eligible women were found and complete interviews were obtained with 98 percent of these women.
Note: See summarized response rates by place of residence in Table 1.2 of the survey report.
The results from sample surveys are affected by two types of errors, non-sampling error and sampling error. Non-sampling error is due to mistakes made in carrying out field activities, such as failure to locate and interview the correct household, errors in the way the questions are asked, misunderstanding on the part of either the interviewer or the respondent, data entry errors, etc. Although efforts were made during the design and implementation of the IDHS to minimize this type of error, non-sampling errors are impossible to avoid and difficult to evaluate analytically.
Sampling errors, on the other hand, can be measured statistically. The sample of women selected in the IDHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each one would have yielded results that differed somewhat from the actual sample selected. The sampling error is a measure of the variability between all possible samples; although it is not known exactly, it can be estimated from the survey results. Sampling error is usually measured in terms of standard error of 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 one can reasonably be assured that, apart from non-sampling errors, the true value of the variable for the whole population falls. For example, for any given statistic calculated from a sample survey, the value of that same statistic as measured in 95 percent of all possible samples with the same design (and expected size) will fall within a range of plus or minus two times the standard error of that statistic.
If the sample of women had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the IDHS sample design depended on stratification, stages and clusters. Consequently, it was necessary to utilize more complex formulas. The computer package CLUSTERS, developed by the International Statistical Institute for the World Fertility Survey, was used to assist in computing the sampling errors with the proper statistical methodology.
Note: See detailed estimate of sampling error calculation in APPENDIX B of the survey report.
Data Quality Tables - Household age distribution - Age distribution of eligible and interviewed women - Completeness of reporting - Births by calendar year since birth - 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.
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Professional organizations in STEM (science, technology, engineering, and mathematics) can use demographic data to quantify recruitment and retention (R&R) of underrepresented groups within their memberships. However, variation in the types of demographic data collected can influence the targeting and perceived impacts of R&R efforts - e.g., giving false signals of R&R for some groups. We obtained demographic surveys from 73 U.S.-affiliated STEM organizations, collectively representing 712,000 members and conference-attendees. We found large differences in the demographic categories surveyed (e.g., disability status, sexual orientation) and the available response options. These discrepancies indicate a lack of consensus regarding the demographic groups that should be recognized and, for groups that are omitted from surveys, an inability of organizations to prioritize and evaluate R&R initiatives. Aligning inclusive demographic surveys across organizations will provide baseline data that can be used to target and evaluate R&R initiatives to better serve underrepresented groups throughout STEM. Methods We surveyed 164 STEM organizations (73 responses, rate = 44.5%) between December 2020 and July 2021 with the goal of understanding what demographic data each organization collects from its constituents (i.e., members and conference-attendees) and how the data are used. Organizations were sourced from a list of professional societies affiliated with the American Association for the Advancement of Science, AAAS, (n = 156) or from social media (n = 8). The survey was sent to the elected leadership and management firms for each organization, and follow-up reminders were sent after one month. The responding organizations represented a wide range of fields: 31 life science organizations (157,000 constituents), 5 mathematics organizations (93,000 constituents), 16 physical science organizations (207,000 constituents), 7 technology organizations (124,000 constituents), and 14 multi-disciplinary organizations spanning multiple branches of STEM (131,000 constituents). A list of the responding organizations is available in the Supplementary Materials. Based on the AAAS-affiliated recruitment of the organizations and the similar distribution of constituencies across STEM fields, we conclude that the responding organizations are a representative cross-section of the most prominent STEM organizations in the U.S. Each organization was asked about the demographic information they collect from their constituents, the response rates to their surveys, and how the data were used. Survey description The following questions are written as presented to the participating organizations. Question 1: What is the name of your STEM organization? Question 2: Does your organization collect demographic data from your membership and/or meeting attendees? Question 3: When was your organization’s most recent demographic survey (approximate year)? Question 4: We would like to know the categories of demographic information collected by your organization. You may answer this question by either uploading a blank copy of your organization’s survey (linked provided in online version of this survey) OR by completing a short series of questions. Question 5: On the most recent demographic survey or questionnaire, what categories of information were collected? (Please select all that apply)
Disability status Gender identity (e.g., male, female, non-binary) Marital/Family status Racial and ethnic group Religion Sex Sexual orientation Veteran status Other (please provide)
Question 6: For each of the categories selected in Question 5, what options were provided for survey participants to select? Question 7: Did the most recent demographic survey provide a statement about data privacy and confidentiality? If yes, please provide the statement. Question 8: Did the most recent demographic survey provide a statement about intended data use? If yes, please provide the statement. Question 9: Who maintains the demographic data collected by your organization? (e.g., contracted third party, organization executives) Question 10: How has your organization used members’ demographic data in the last five years? Examples: monitoring temporal changes in demographic diversity, publishing diversity data products, planning conferences, contributing to third-party researchers. Question 11: What is the size of your organization (number of members or number of attendees at recent meetings)? Question 12: What was the response rate (%) for your organization’s most recent demographic survey? *Organizations were also able to upload a copy of their demographics survey instead of responding to Questions 5-8. If so, the uploaded survey was used (by the study authors) to evaluate Questions 5-8.