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Emergency medical services (EMS) workforce demographics in the United States do not reflect the diversity of the population served. Despite some efforts by professional organizations to create a more representative workforce, little has changed in the last decade. This scoping review aims to summarize existing literature on the demographic composition, recruitment, retention, and workplace experience of underrepresented groups within EMS. Peer-reviewed studies were obtained from a search of PubMed, CINAHL, Web of Science, ProQuest Thesis and Dissertations, and non-peer-reviewed (“gray”) literature from 1960 to present. Abstracts and included full-text articles were screened by two independent reviewers trained on inclusion/exclusion criteria. Studies were included if they pertained to the demographics, training, hiring, retention, promotion, compensation, or workplace experience of underrepresented groups in United States EMS by race, ethnicity, sexual orientation, or gender. Studies of non-EMS fire department activities were excluded. Disputes were resolved by two authors. A single reviewer screened the gray literature. Data extraction was performed using a standardized electronic form. Results were summarized qualitatively. We identified 87 relevant full-text articles from the peer-reviewed literature and 250 items of gray literature. Primary themes emerging from peer-reviewed literature included workplace experience (n = 48), demographics (n = 12), workforce entry and exit (n = 8), education and testing (n = 7), compensation and benefits (n = 5), and leadership, mentorship, and promotion (n = 4). Most articles focused on sex/gender comparisons (65/87, 75%), followed by race/ethnicity comparisons (42/87, 48%). Few articles examined sexual orientation (3/87, 3%). One study focused on telecommunicators and three included EMS physicians. Most studies (n = 60, 69%) were published in the last decade. In the gray literature, media articles (216/250, 86%) demonstrated significant industry discourse surrounding these primary themes. Existing EMS workforce research demonstrates continued underrepresentation of women and nonwhite personnel. Additionally, these studies raise concerns for pervasive negative workplace experiences including sexual harassment and factors that negatively affect recruitment and retention, including bias in candidate testing, a gender pay gap, and unequal promotion opportunities. Additional research is needed to elucidate recruitment and retention program efficacy, the demographic composition of EMS leadership, and the prevalence of racial harassment and discrimination in this workforce.
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As per our latest research, the global Clinical Trial Patient Injury Insurance market size in 2024 stands at USD 2.14 billion. The market is experiencing a robust growth trajectory, registering a CAGR of 7.8% from 2025 to 2033. By the end of 2033, the market is forecasted to reach USD 4.23 billion. This impressive growth is primarily driven by the escalating number of clinical trials worldwide, increasing regulatory requirements for patient safety, and the rising complexity of clinical research protocols.
The growth of the Clinical Trial Patient Injury Insurance market is fundamentally underpinned by the rapid expansion of the global clinical trials landscape. Pharmaceutical and biotechnology companies are increasingly investing in research and development to bring innovative therapies to market, leading to a surge in the number of clinical trials. Regulatory authorities in major markets such as the United States, Europe, and Asia Pacific have instituted stringent guidelines mandating insurance coverage for trial participants to ensure their safety and well-being. This regulatory push is compelling sponsors to secure comprehensive patient injury insurance, thereby fueling market expansion. Furthermore, the growing prevalence of complex and high-risk clinical trials, especially those involving novel therapies like gene editing and immunotherapies, is amplifying the demand for specialized insurance products tailored to these risks.
Another significant growth factor is the heightened awareness and advocacy for patient rights and safety within the clinical research ecosystem. Patient advocacy groups, ethical review boards, and regulatory bodies are increasingly emphasizing the need for robust protection mechanisms for participants in clinical trials. This has led to the proliferation of insurance solutions that provide coverage for a wide range of injuries, disabilities, and even death resulting from participation in clinical studies. Additionally, the globalization of clinical research has resulted in trials being conducted across diverse geographies, including emerging markets where insurance penetration was historically low. This trend is driving insurance providers to develop region-specific products that cater to local regulatory requirements and patient demographics, thereby expanding the market’s reach and diversity.
Technological advancements and digital transformation in the insurance sector are also contributing to the market’s growth. The adoption of digital platforms, AI-driven underwriting, and real-time claims processing is enhancing the efficiency and transparency of clinical trial patient injury insurance. These innovations are not only streamlining the insurance procurement process for sponsors and contract research organizations (CROs) but also improving the overall experience for insured patients. Furthermore, the entry of insurtech companies and the development of online distribution channels are making insurance products more accessible and customizable. This digital shift is expected to further accelerate market growth by lowering administrative barriers and reducing costs associated with traditional insurance models.
From a regional perspective, North America continues to dominate the Clinical Trial Patient Injury Insurance market, owing to its advanced healthcare infrastructure, high volume of clinical research activities, and stringent regulatory environment. Europe follows closely, driven by harmonized regulations under the European Union Clinical Trials Regulation (EU CTR) and a strong presence of pharmaceutical and biotechnology industries. The Asia Pacific region is emerging as a high-growth market, propelled by increasing investments in clinical research, expanding healthcare infrastructure, and growing adoption of insurance solutions. Latin America and the Middle East & Africa, while currently representing smaller market shares, are witnessing gradual growth as clinical trial activities and regulatory oversight increase in these regions.
The Clinical Trial Patient Injury Insurance market can be segmented by type into Individual Insurance and Group Insurance. Individual insurance policies are tailored to cover specific participants in a clinical trial. This segment is particularly significant for trials involving high-risk procedures or vulnerable patient populations, where the likelihood of adverse events is higher. Individual insur
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Profile of psychiatric symptoms among people with schizophrenia and attending the follow-up service at Jimma University Medical Center, psychiatric clinic (n = 351).
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TwitterThe 2013 NDHS is part of the worldwide Demographic and Health Surveys (DHS) programme funded by the United States Agency for International Development (USAID). DHS surveys are designed to collect data on fertility, family planning, and maternal and child health; assist countries in monitoring changes in population, health, and nutrition; and provide an international database that can be used by researchers investigating topics related to population, health, and nutrition.
The overall objective of the survey is to provide demographic, socioeconomic, and health data necessary for policymaking, planning, monitoring, and evaluation of national health and population programmes. In addition, the survey measured the prevalence of anaemia, HIV, high blood glucose, and high blood pressure among adult women and men; assessed the prevalence of anaemia among children age 6-59 months; and collected anthropometric measurements to assess the nutritional status of women, men, and children.
A long-term objective of the survey is to strengthen the technical capacity of local organizations to plan, conduct, and process and analyse data from complex national population and health surveys. At the global level, the 2013 NDHS data are comparable with those from a number of DHS surveys conducted in other developing countries. The 2013 NDHS adds to the vast and growing international database on demographic and health-related variables.
National coverage
Sample survey data [ssd]
Sample Design The primary focus of the 2013 NDHS 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. In addition, the sample was designed to provide estimates of most key variables for the 13 administrative regions.
Each of the administrative regions is subdivided into a number of constituencies (with an overall total of 107 constituencies). Each constituency is further subdivided into lower level administrative units. An enumeration area (EA) is the smallest identifiable entity without administrative specification, numbered sequentially within each constituency. Each EA is classified as urban or rural. The sampling frame used for the 2013 NDHS was the preliminary frame of the 2011 Namibia Population and Housing Census (NSA, 2013a). The sampling frame was a complete list of all EAs covering the whole country. Each EA is a geographical area covering an adequate number of households to serve as a counting unit for the population census. In rural areas, an EA is a natural village, part of a large village, or a group of small villages; in urban areas, an EA is usually a city block. The 2011 population census also produced a digitised map for each of the EAs that served as the means of identifying these areas.
The sample for the 2013 NDHS was a stratified sample selected in two stages. In the first stage, 554 EAs-269 in urban areas and 285 in rural areas-were selected with a stratified probability proportional to size selection from the sampling frame. The size of an EA is defined according to the number of households residing in the EA, as recorded in the 2011 Population and Housing Census. Stratification was achieved by separating every region into urban and rural areas. Therefore, the 13 regions were stratified into 26 sampling strata (13 rural strata and 13 urban strata). Samples were selected independently in every stratum, with a predetermined number of EAs selected. A complete household listing and mapping operation was carried out in all selected clusters. In the second stage, a fixed number of 20 households were selected in every urban and rural cluster according to equal probability systematic sampling.
Due to the non-proportional allocation of the sample to the different regions and the possible differences in response rates, sampling weights are required for any analysis using the 2013 NDHS data to ensure the representativeness of the survey results at the national as well as the regional level. Since the 2013 NDHS sample was a two-stage stratified cluster sample, sampling probabilities were calculated separately for each sampling stage and for each cluster.
See Appendix A in the final report for details
Face-to-face [f2f]
Three questionnaires were administered in the 2013 NDHS: the Household Questionnaire, the Woman’s Questionnaire, and the Man’s Questionnaire. These questionnaires were adapted from the standard DHS6 core questionnaires to reflect the population and health issues relevant to Namibia at a series of meetings with various stakeholders from government ministries and agencies, nongovernmental organisations, and international donors. The final draft of each questionnaire was discussed at a questionnaire design workshop organised by the MoHSS from September 25-28, 2012, in Windhoek. The questionnaires were then translated from English into the six main local languages—Afrikaans, Rukwangali, Oshiwambo, Damara/Nama, Otjiherero, and Silozi—and back translated into English. The questionnaires were finalised after the pretest, which took place from February 11-25, 2013.
The Household Questionnaire was used to list all usual household members as well as visitors in the selected households. 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, parents’ survival status was determined. In addition, the Household Questionnaire included questions on knowledge of malaria and use of mosquito nets by household members, along with questions regarding health expenditures. The Household Questionnaire was used to identify women and men who were eligible for the individual interview and the interview on domestic violence. The 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, and ownership of various durable goods. The results of tests assessing iodine levels were recorded as well.
In half of the survey households (the same households selected for the male survey), the Household Questionnaire was also used to record information on anthropometry and biomarker data collected from eligible respondents, as follows: • All eligible women and men age 15-64 were measured, weighed, and tested for anaemia and HIV. • All eligible women and men age 35-64 had their blood pressure and blood glucose measured. • All children age 0 to 59 months were measured and weighed. • All children age 6 to 59 months were tested for anaemia.
The Woman’s Questionnaire was also used to collect information from women age 50-64 living in half of the selected survey households on background characteristics, marriage and sexual activity, women’s work and husbands’ background characteristics, awareness and behaviour regarding AIDS and other STIs, and other health issues.
The Man’s Questionnaire was administered to all men age 15-64 living in half of the selected survey households. The Man’s Questionnaire collected much of the same information as 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.
CSPro—a Windows-based integrated census and survey processing system that combines and replaces the ISSA and IMPS packages—was used for entry, editing, and tabulation of the NDHS data. Prior to data entry, a practical training session was provided by ICF International to all data entry staff. A total of 28 data processing personnel, including 17 data entry operators, one questionnaire administrator, two office editors, three secondary editors, two network technicians, two data processing supervisors, and one coordinator, were recruited and trained on administration of questionnaires and coding, data entry and verification, correction of questionnaires and provision of feedback, and secondary editing. NDHS data processing was formally launched during the week of June 22, 2013, at the National Statistics Agency Data Processing Centre in Windhoek. The data entry and editing phase of the survey was completed in January 2014.
A total of 11,004 households were selected for the sample, of which 10,165 were found to be occupied during data collection. Of the occupied households, 9,849 were successfully interviewed, yielding a household response rate of 97 percent.
In these households, 9,940 women age 15-49 were identified as eligible for the individual interview. Interviews were completed with 9,176 women, yielding a response rate of 92 percent. In addition, in half of these households, 842 women age 50-64 were successfully interviewed; in this group of women, the response rate was 91 percent.
Of the 5,271 eligible men identified in the selected subsample of households, 4,481 (85 percent) were successfully interviewed.
Response rates were higher in rural than in urban areas, with the rural-urban difference more marked among men than among women.
The estimates from a sample survey are affected by two types of errors: nonsampling errors and sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview
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TwitterThe 2015-16 Armenia Demographic and Health Survey (2015-16 ADHS) is the fourth in a series of nationally representative sample surveys designed to provide information on population and health issues. It is conducted in Armenia under the worldwide Demographic and Health Surveys program. Specifically, the objective of the 2015-16 ADHS is to provide current and reliable information on fertility and abortion levels, marriage, sexual activity, fertility preferences, awareness and use of family planning methods, breastfeeding practices, nutritional status of young children, childhood mortality, maternal and child health, domestic violence against women, child discipline, awareness and behavior regarding AIDS and other sexually transmitted infections (STIs), and other health-related issues such as smoking, tuberculosis, and anemia. The survey obtained detailed information on these issues from women of reproductive age and, for certain topics, from men as well.
The 2015-16 ADHS results are intended to provide information needed to evaluate existing social programs and to design new strategies to improve the health of and health services for the people of Armenia. Data are presented by region (marz) wherever sample size permits. The information collected in the 2015-16 ADHS will provide updated estimates of basic demographic and health indicators covered in the 2000, 2005, and 2010 surveys.
The long-term objective of the survey includes strengthening the technical capacity of major government institutions, including the NSS. The 2015-16 ADHS also provides comparable data for longterm trend analysis because the 2000, 2005, 2010, and 2015-16 surveys were implemented by the same organization and used similar data collection procedures. It also adds to the international database of demographic and health–related information for research purposes.
National coverage
The survey covered all de jure household members (usual residents), children age 0-4 years, women age 15-49 years and men age 15-49 years resident in the household.
Sample survey data [ssd]
The sample was designed to produce representative estimates of key indicators at the national level, for Yerevan, and for total urban and total rural areas separately. Many indicators can also be estimated at the regional (marz) level.
The sampling frame used for the 2015-16 ADHS is the Armenia Population and Housing Census, which was conducted in Armenia in 2011 (APHC 2011). The sampling frame is a complete list of enumeration areas (EAs) covering the whole country, a total number of 11,571 EAs, provided by the National Statistical Service (NSS) of Armenia, the implementing agency for the 2015-16 ADHS. This EA frame was created from the census data base by summarizing the households down to EA level. A representative probability sample of 8,749 households was selected for the 2015-16 ADHS sample. The sample was selected in two stages. In the first stage, 313 clusters (192 in urban areas and 121 in rural areas) were selected from a list of EAs in the sampling frame. In the second stage, a complete listing of households was carried out in each selected cluster. Households were then systematically selected for participation in the survey. Appendix A provides additional information on the sample design of the 2015-16 Armenia DHS. Because of the approximately equal sample size in each marz, the sample is not self-weighting at the national level, and weighting factors have been calculated, added to the data file, and applied so that results are representative at the national level.
For further details on sample design, see Appendix A of the final report.
Face-to-face [f2f]
Five questionnaires were used for the 2015-16 ADHS: the Household Questionnaire, the Woman’s Questionnaire, the Man’s Questionnaire, the Biomarker Questionnaire, and the Fieldworker Questionnaire. These questionnaires, based on The DHS Program’s standard Demographic and Health Survey questionnaires, were adapted to reflect the population and health issues relevant to Armenia. Input was solicited from various stakeholders representing government ministries and agencies, nongovernmental organizations, and international donors. After all questionnaires were finalized in English, they were translated into Armenian. They were pretested in September-October 2015.
The processing of the 2015-16 ADHS data began shortly after fieldwork commenced. All completed questionnaires were edited immediately by field editors while still in the field and checked by the supervisors before being dispatched to the data processing center at the NSS central office in Yerevan. These completed questionnaires were edited and entered by 15 data processing personnel specially trained for this task. All data were entered twice for 100 percent verification. Data were entered using the CSPro computer package. The concurrent processing of the data was an advantage because the senior ADHS technical staff were able to advise field teams of problems detected during the data entry. In particular, tables were generated to check various data quality parameters. Moreover, the double entry of data enabled easy comparison and identification of errors and inconsistencies. As a result, specific feedback was given to the teams to improve performance. The data entry and editing phase of the survey was completed in June 2016.
A total of 8,749 households were selected in the sample, of which 8,205 were occupied at the time of the fieldwork. The main reason for the difference is that some of the dwelling units that were occupied during the household listing operation were either vacant or the household was away for an extended period at the time of interviewing. The number of occupied households successfully interviewed was 7,893, yielding a household response rate of 96 percent. The household response rate in urban areas (96 percent) was nearly the same as in rural areas (97 percent).
In these households, a total of 6,251 eligible women were identified; interviews were completed with 6,116 of these women, yielding a response rate of 98 percent. In one-half of the households, a total of 2,856 eligible men were identified, and interviews were completed with 2,755 of these men, yielding a response rate of 97 percent. Among men, response rates are slightly lower in urban areas (96 percent) than in rural areas (97 percent), whereas rates for women are the same in urban and in rural areas (98 percent).
The 2015-16 ADHS achieved a slightly higher response rate for households than the 2010 ADHS (NSS 2012). The increase is only notable for urban households (96 percent in 2015-16 compared with 94 percent in 2010). Response rates in all other categories are very close to what they were in 2010.
SAS computer software were used to calculate sampling errors for the 2015-16 ADHS. The programs used the Taylor linearization method of variance estimation for means or proportions and the Jackknife repeated replication method for variance estimation of more complex statistics such as fertility and mortality rates.
A more detailed description of estimates of sampling errors are presented in Appendix B of the survey final report.
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 - Nutritional status of children based on the NCHS/CDC/WHO International Reference Population - Vaccinations by background characteristics for children age 18-29 months
See details of the data quality tables in Appendix C of the survey final report.
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The air medical emergency transport market, valued at $408 million in 2025, is projected to experience robust growth, driven by several key factors. Rising incidences of critical illnesses and injuries, coupled with an aging global population requiring more specialized medical care, are significantly boosting demand. Technological advancements, such as the integration of advanced medical equipment and telemedicine capabilities within air ambulances, are enhancing the quality of care and expanding the scope of services. Furthermore, increasing government initiatives to improve emergency medical services infrastructure and growing private insurance coverage for air medical transport are contributing to market expansion. The competitive landscape is characterized by a mix of established players like AirMed and Air Ambulance Worldwide, and smaller regional operators, indicating both established market share and opportunities for emerging companies. The market's growth trajectory is expected to remain positive, albeit with potential regional variations due to differing healthcare infrastructure and economic conditions. This growth, however, faces certain challenges. High operational costs associated with aircraft maintenance, pilot salaries, and specialized medical equipment pose a barrier to market entry and limit profitability for smaller operators. Strict regulatory frameworks and safety standards necessitate substantial investment in compliance, adding further complexity. Fluctuations in fuel prices also present a significant risk to profitability, impacting the pricing strategies of providers. Despite these challenges, the long-term outlook remains positive, with consistent growth expected throughout the forecast period (2025-2033) due to the underlying demographic and technological factors. Market segmentation analysis, though not explicitly provided, likely reflects variations in service type (e.g., helicopter vs. fixed-wing), patient demographics (e.g., trauma vs. organ transport), and geographic reach. This suggests further opportunities for specialization and market penetration within this evolving sector.
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TwitterThe IDHS 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 2007 IDHS was to provide detailed information on population, family planning, and health for policymakers and program managers. The 2007 IDHS was conducted in all 33 provinces in Indonesia. The survey collected information on respondents’ socioeconomic background, fertility levels, marriage and sexual activity, fertility preferences, knowledge and use of family planning methods, breastfeeding practices, childhood and adult mortality including maternal mortality, maternal and child health, and awareness and behavior regarding HIV/AIDS and other sexually-transmitted infections.
The 2007 IDHS was specifically designed to meet the following objectives: - Provide data concerning fertility, family planning, maternal and child health, 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, analyze factors that affect such changes, such as marital status and patterns, residence, education, breastfeeding habits, and knowledge, use, and availability of contraception.; - Evaluate achievement of goals previously set by the national health programs, with special focus on maternal and child health; - Assess men’s participation and utilization of health services, as well as of their families; - Assist in creating an international database that allows cross-country comparisons that can be used by the program managers, policymakers, and researchers in the area of family planning, fertility, and health in general.
National
Sample survey data
Administratively, 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 2007 IDHS sample is designed to provide estimates with acceptable precision for the following domains: - Indonesia as a whole; - Each of 33 provinces covered in the survey, and - Urban and rural areas of Indonesia
The census blocks (CBs) are the primary sampling unit for the 2007 IDHS. The sample developed for the 2007 National Labor Force Survey (Sakernas) was used as a frame for the selection of the 2007 IDHS sample. Household listing was done in all CBs covered in the 2007 Sakernas. This eliminates the need to conduct a separate household listing for the 2007 IDHS.
A minimum of 40 CBs per province has been imposed in the 2007 IDHS design. Since the sample was designed to provide reliable indicators for each province, the number of CBs in each province was not allocated proportional to the population of the province nor proportional by urban-rural classification. Therefore, a final weighing adjustment procedure was done to obtain estimates for all domains.
The 2007 IDHS sample is selected using a stratified two-stage design consisting of 1,694 CBs. Once the number of households was allocated to each province by urban and rural areas, the number of CBs was calculated based on an average sample take of 25 selected households. All evermarried women age 15-49 and all unmarried persons age 15-24 in these households are eligible for individual interview. Eight households in each CB selected for the women sample were selected for male interview.
Note: See detailed description of sample design in APPENDIX B of the survey report.
Face-to-face [f2f]
The 2007 IDHS used three questionnaires: the Household Questionnaire (HQ), the Ever-Married Women’s Questionnaire (EMWQ) and the Married Men’s Questionnaire (MMQ). In consultation with BKKBN and MOH, BPS made a decision to base the 2007 IDHS survey instruments largely on the questionnaires used in the 2002-03 IDHS to facilitate trend analysis. Input was solicited from other potential data users, and several modifications were made to optimize the draft 2007 IDHS instruments to collect the needs for population and health data. The draft IDHS questionnaires were also compared with the most recent version of the standard questionnaires used in the DHS program and minor modifications incorporated to facilitate international comparison.
The HQ was used to list all the usual members and visitors in the selected households. Basic information collected on each person listed includes: age, sex, education, and relationship to the head of the household. The main purpose of the HQ was to identify women and men who were eligible for the individual interview. Information on characteristics of the household’s dwelling unit, such as the source of water, type of toilet facilities, construction materials used for the floor and outer walls of the house, and ownership of various durable goods were also recorded in the HQ. These items reflect the household’s socioeconomic status.
The EMWQ was used to collect information from all ever-married women age 15-49. These women were asked questions on the following topics:: - Background characteristics (marital status, education, media exposure, etc.) - Knowledge and use of family planning methods - Reproductive history and fertility preferences - Antenatal, delivery and postnatal care - Breastfeeding and infant feeding practices - Vaccinations and childhood illnesses - Practices related to the malaria prevention - Marriage and sexual activity - Woman’s work and husband’s background characteristics - Infant’s and children’s feeding practices - Childhood mortality - Awareness and behavior regarding AIDS and other sexually transmitted infections (STIs) - Sibling mortality, including maternal mortality.
The MMQ was administered to all currently married men age 15-54 living in every third household in the IDHS sample. The MMQ collected much of the same information included in the EMWQ, but was shorter because it did not contain questions on reproductive history, maternal and child health, nutrition and maternal mortality. Instead, men were asked about their knowledge and participation in health-care-seeking practices for their children.
All completed questionnaires for the IDHS, accompanied by their control forms, were returned to the BPS central office in Jakarta for data processing. This consisted of office editing, coding of openended questions, data entry, verification, and editing computer-identified errors. A team of 42 data entry clerks, data editors and data entry supervisors processed the data. Data entry and editing was carried using a computer package program called CSPro, which was specifically designed to process DHS-type survey data. During the preparation of the data entry programs, a BPS staff spent several weeks at ORC Macro offices in Calverton, Maryland. Data entry and editing activities, which began in September, 2007 were completed in March 2008.
In general, the response rates for both the household and individual interviews in the 2007 IDHS are high. A total of 42,341 households were selected in the sample, of which 41,131 were occupied. Of these households, 40,701 were successfully interviewed, yielding a household response rate of 99 percent.
In the interviewed households, 34,227 women were identified for individual interview and of these completed interviews were conducted with 32,895 women, yielding a response rate of 96 percent. In a third of the households, 9,716 eligible men were identified, of which 8,758 were successfully interviewed, yielding a response rate of 90 percent. The lower response rate for men was due to the more frequent and longer absence of men from the household.
Note: See summarized response rates by place of residence in Table 1.2 of the survey report.
The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors, and (2) sampling errors. Nonsampling errors are the results of 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 2007 Indonesia Demographic and Health Survey (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 2007 IDHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.
A sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall.
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TwitterThe Indonesia Demographic and Health Survey (IDHS) 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 2002-2003 IDHS follows a sequence of several previous surveys: the 1987 National Indonesia Contraceptive Prevalence Survey (NICPS), the 1991 IDHS, the 1994 IDHS, and the 1997 IDHS. The 2002-2003 IDHS is expanded from the 1997 IDHS by including a collection of information on the participation of currently married men and their wives and children in the health care.
The main objective of the 2002-2003 IDHS is to provide policymakers and program managers in population and health with detailed information on population, family planning, and health. In particular, the 2002-2003 IDHS collected information on the female respondents’ socioeconomic background, fertility levels, marriage and sexual activity, fertility preferences, knowledge and use of family planning methods, breastfeeding practices, childhood and adult mortality including maternal mortality, maternal and child health, and awareness and behavior regarding AIDS and other sexually transmitted infections in Indonesia.
The 2002-2003 IDHS was specifically designed to meet the following objectives: - Provide data concerning fertility, family planning, maternal and child health, 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, analyze factors that affect such changes, such as marital status and patterns, residence, education, breastfeeding habits, and knowledge, use, and availability of contraception - Evaluate achievement of goals previously set by the national health programs, with special focus on maternal and child health - Assess men’s participation and utilization of health services, as well as of their families - Assist in creating an international database that allows cross-country comparisons that can be used by the program managers, policymakers, and researchers in the area of family planning, fertility, and health in general.
National
Sample survey data
SAMPLE DESIGN AND IMPLEMENTATION
Administratively, Indonesia is divided into 30 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 primary objective of the 2002-2003 IDHS is to provide estimates with acceptable precision for the following domains: · Indonesia as a whole; · Each of 26 provinces covered in the survey. The four provinces excluded due to political instability are Nanggroe Aceh Darussalam, Maluku, North Maluku and Papua. These provinces cover 4 percent of the total population. · Urban and rural areas of Indonesia; · Each of the five districts in Central Java and the five districts in East Java covered in the Safe Motherhood Project (SMP), to provide information for the monitoring and evaluation of the project. These districts are: - in Central Java: Cilacap, Rembang, Jepara, Pemalang, and Brebes. - in East Java: Trenggalek, Jombang, Ngawi, Sampang and Pamekasan.
The census blocks (CBs) are the primary sampling unit for the 2002-2003 IDHS. CBs were formed during the preparation of the 2000 Population Census. Each CB includes approximately 80 households. In the master sample frame, the CBs are grouped by province, by regency/municipality within a province, and by subdistricts within a regency/municipality. In rural areas, the CBs in each district are listed by their geographical location. In urban areas, the CBs are distinguished by the urban classification (large, medium and small cities) in each subdistrict.
Note: See detailed description of sample design in APPENDIX B of the survey report.
Face-to-face
The 2002-2003 IDHS used three questionnaires: the Household Questionnaire, the Women’s Questionnaire for ever-married women 15-49 years old, and the Men’s Questionnaire for currently married men 15-54 years old. The Household Questionnaire and the Women’s Questionnaire were based on the DHS Model “A” Questionnaire, which is designed for use in countries with high contraceptive prevalence. In consultation with the NFPCB and MOH, BPS modified these questionnaires to reflect relevant issues in family planning and health in Indonesia. Inputs were also solicited from potential data users to optimize the IDHS in meeting the country’s needs for population and health data. The questionnaires were translated from English into the national language, Bahasa Indonesia.
The Household Questionnaire was used to list all the usual members and visitors in the selected households. Basic information collected for each person listed includes the following: 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 the individual interview. In addition, the Household Questionnaire also identifies unmarried women and men age 15-24 who are eligible for the individual interview in the Indonesia Young Adult Reproductive Health Survey (IYARHS). Information on characteristics of the household’s dwelling unit, such as the source of water, type of toilet facilities, construction materials used for the floor 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.
The Women’s Questionnaire was used to collect information from all ever-married women age 15-49. These women were asked questions on the following topics: • Background characteristics, such as age, marital status, education, and media exposure • Knowledge and use of family planning methods • Fertility preferences • Antenatal, delivery, and postnatal care • Breastfeeding and infant feeding practices • Vaccinations and childhood illnesses • Marriage and sexual activity • Woman’s work and husband’s background characteristics • Childhood mortality • Awareness and behavior regarding AIDS and other sexually transmitted infections (STIs) • Sibling mortality, including maternal mortality.
The Men’s Questionnaire was administered to all currently married men age 15-54 in every third household in the IDHS sample. The Men’s Questionnaire collected much of the same information included in the Women’s Questionnaire, but was shorter because it did not contain questions on reproductive history, maternal and child health, nutrition, and maternal mortality. Instead, men were asked about their knowledge and participation in the health-seeking practices for their children.
All completed questionnaires for IDHS, accompanied by their control forms, were returned to the BPS central office in Jakarta for data processing. This process consisted of office editing, coding of open-ended questions, data entry, verification, and editing computer-identified errors. A team of about 40 data entry clerks, data editors, and two data entry supervisors processed the data. Data entry and editing started on November 4, 2002 using a computer package program called CSPro, which was specifically designed to process DHS-type survey data. To prepare the data entry programs, two BPS staff spent three weeks in ORC Macro offices in Calverton, Maryland in April 2002.
A total of 34,738 households were selected for the survey, of which 33,419 were found. Of the encountered households, 33,088 (99 percent) were successfully interviewed. In these households, 29,996 ever-married women 15-49 were identified, and complete interviews were obtained from 29,483 of them (98 percent). From the households selected for interviews with men, 8,740 currently married men 15-54 were identified, and complete interviews were obtained from 8,310 men, or 95 percent of all eligible men. The generally high response rates for both household and individual interviews (for eligible women and men) were due mainly to the strict enforcement of the rule to revisit the originally selected household if no one was at home initially. No substitution for the originally selected households was allowed. Interviewers were instructed to make at least three visits in an effort to contact the household, eligible women, and eligible men.
Note: See summarized response rates by place of residence in Table 1.2 of the survey report.
The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors, and (2) sampling errors. Nonsampling errors are the results of 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 2002-2003 Indonesia Demographic and Health Survey (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
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Data for this publication are extracted each month as a snapshot in time from the Primary Care Registration database within the NHAIS (National Health Application and Infrastructure Services) system. This release is an accurate snapshot as at 1 January 2021. GP Practice; Primary Care Network (PCN); Sustainability and transformation partnership (STP); Clinical Commissioning Group (CCG) and NHS England Commissioning Region level data are released in single year of age (SYOA) and 5-year age bands, both of which finish at 95+, split by gender. In addition, organisational mapping data is available to derive STP; PCN; CCG and Commissioning Region associated with a GP practice and is updated each month to give relevant organisational mapping. Quarterly publications in January, April, July and October will include Lower Layer Super Output Area (LSOA) populations and a spotlight report. The outbreak of Coronavirus (COVID-19) has led to changes in the work of General Practices and subsequently the data within this publication. Until activity in this healthcare setting stabilises, we urge caution in drawing any conclusions from these data without consideration of the country's circumstances and would recommend that any uses of these data are accompanied by an appropriate caveat. Note: An error was identified on 20/1/2021 in the practice mapping file where practices had duplicate entries for different extract dates. This has now been corrected so that each practice has one extract date. The mapping file has been replaced and is therefore affixed with '_v2' to reflect this. This error does not affect the patients registered at a GP practice data itself.
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TwitterThe National Ambulatory Medical Care Surveys (NAMCS) supply data on ambulatory medical care provided in physicians' offices. The 2003 survey contains information from 28,738 patient visits to 1,215 physicians' offices. Data are available on the patient's smoking habits, reason for the visit, expected source of payment, the physician's diagnosis, and the kinds of diagnostic and therapeutic services rendered. Other variables cover drugs/medications ordered, administered, or provided during office visits, with information on medication code, generic name and code, brand name, entry status, prescription status, federal controlled substance status, composition status, and related ingredient codes. Information is also included on the physician's specialization and geographic location. Demographic information on patients, such as age, sex, race, and ethnicity, was also collected.
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TwitterThe 2006 Azerbaijan Demographic and Health Survey (2006 AzDHS) is a nationally representative sample survey designed to provide information on population and health issues in Azerbaijan. The primary goal of the survey was to develop a single integrated set of demographic and health data pertaining to the population of the Republic of Azerbaijan.
The 2006 AzDHS was conducted from July to November by the State Statistical Committee (SSC) of the Republic of Azerbaijan. Macro International Inc. provided technical support for the survey through the MEASURE DHS project. USAID Caucasus, Azerbaijan provided funding for the survey through the MEASURE DHS project. MEASURE DHS is sponsored by the United States Agency for International Development (USAID) to assist countries worldwide in obtaining information on key population and health indicators. The UNICEF/Azerbaijan country office was instrumental for political mobilization during the early stages of the 2006 AzDHS negotiation with the Government of Azerbaijan and also supported the survey through in-kind contributions.
The 2006 AzDHS collected national- and regional-level data on fertility and contraceptive use, maternal and child health, adult health, tuberculosis, and HIV/AIDS and other sexually transmitted diseases. The survey obtained detailed information on these issues from women of reproductive age and, on certain topics, from men as well.
The 2006 AzDHS results are intended to provide the information needed to evaluate existing social programs and to design new strategies for improving the health of Azerbaijanis and health services for the people of Azerbaijan. The 2006 AzDHS also contributes to the growing international database on demographic and health-related variables.
The 2006 Azerbaijan Demographic and Health Survey (2006 AzDHS) is a nationally representative sample survey.
Sample survey data
The sample was designed to permit detailed analysis, including the estimation of rates of fertility, infant/child mortality, and abortion, for the national level, for Baku, and for urban and rural areas separately. Many indicators are available separately for each of the economic regions in Azerbaijan except the Autonomous Republic of Nakhichevan (conducting the survey in Nakhichevan was complicated, since this region is in the blockade).
A representative probability sample of households was selected for the 2006 AzDHS sample. The sample was selected in two stages. In the first stage, 318 clusters in Baku and 8 other economic regions were selected from a list of enumeration areas from the master sample frame that was designed for the 1999 Population Census. In the second stage, a complete listing of households was carried out in each selected cluster. Households were then systematically selected from each cluster for participation in the survey. This design resulted in a final sample of 7,619 households.
Because of the non-proportional allocation of the sample to the different economic regions, sampling weights will be required in all analysis using the DHS data to ensure the actual representativity of the sample at both the national and regional levels. The sampling weight for each household is the inverse of its overall selection probability with correction for household non-response; the individual weight is the household weight with correction of individual non-response. Sampling weights are further normalized in order to give the total number of unweighted cases equal to the total number of weighted cases at the national level, for both household weights and individual weights.
All women age 15-49 who were either permanent residents of the households in the 2006 AzDHS sample or visitors present in the household on the night before the survey were eligible to be interviewed. In addition, all men age 15-59 in one-third of the households selected for the survey were eligible to be interviewed if they were either permanent residents or visitors present in the household on the night before the survey. Interviews were completed with 8,444 women and 2,558 men.
Note: See detailed description of sample design in APPENDIX A of the Final Report.
Face-to-face [f2f]
Three questionnaires were used in the AzDHS: Household Questionnaire, Women’s Questionnaire, and Men’s Questionnaire. The household and individual questionnaires were based on model survey instruments developed in the MEASURE DHS program. The model questionnaires were adapted for use by experts from the SSC and Ministry of Health (MOH). Input was also sought from a number of nongovernmental organizations. Additionally, at the request of UNICEF, the Multiple Indicator Cluster Survey (MICS) modules on early child education and development, birth registration, and child discipline were adapted for the 2006 AzDHS instrument. The questionnaires were prepared in English and translated into Azerbaijani and Russian. The household and individual questionnaires were pretested in May 2006.
The Household Questionnaire was used to list all usual members of and visitors to the selected households and to collect information on the socioeconomic status of the household. The first part of the Household Questionnaire collected information on the age, sex, educational attainment, and relationship of each household member or visitor to the household. This information provides basic demographic data for Azerbaijan households. It also was used to identify the women and men who were eligible for the individual interview (i.e., women age 15-49 and men age 15-59). In the second part of the Household Questionnaire, there were questions on housing characteristics (e.g., the flooring material, the source of water, and the type of toilet facilities), on ownership of a variety of consumer goods, and other questions relating to the socioeconomic status of the household. In addition, the Household Questionnaire was used to obtain information on child discipline, education, and development; to record height and weight measurements of women, men, and children under age five; and to record hemoglobin measurements of women and children under age five.
The Women’s Questionnaire obtained information from women age 15-49 on the following topics:- - Background characteristics - Pregnancy history - Abortion history - Antenatal, delivery, and postnatal care - Knowledge, attitudes, and use of contraception - Reproductive and adult health - Vaccinations, birth registration, and childhood illness and treatment - Breastfeeding and weaning practices - Marriage and recent sexual activity - Fertility preferences - Knowledge of and attitudes toward AIDS and other sexually transmitted diseases - Knowledge of and attitudes toward tuberculosis - Hypertension and other
The Men’s Questionnaire, administered to men age 15-59, covered the following topics: - Background characteristics - Reproductive health - Marriage and recent sexual activity - Attitudes toward and use of condoms - Fertility preferences - Employment and gender roles - Attitudes toward women’s status - Knowledge of and attitudes toward AIDS and other sexually transmitted diseases - Knowledge of and attitudes toward tuberculosis - Hypertension and other adult health issues - Smoking and alcohol consumption
Blood pressure measurements of women and men were recorded in their individual questionnaires.
The processing of the Azerbaijan DHS results began shortly after the fieldwork commenced. Completed questionnaires were returned regularly from the field to SSC headquarters in Baku, where they were entered and edited by data processing personnel who were specially trained for this task. The data processing personnel included a supervisor, a questionnaire administrator, several office editors, 10 data entry operators, and a secondary editor. The concurrent processing of the data was an advantage since the survey technical staff was able to advise field teams of problems detected during the data entry using tables generated to check various data quality parameters. As a result, specific feedback was given to the teams to improve their performance. The data entry and editing phase of the survey was completed in late January 2007.
A total of 7,619 households were selected for the sample, of which 7,341 were found at the time of fieldwork. The main reason for the difference is that some of the dwelling units that were occupied during the household listing operation were either vacant or the household was away for an extended period at the time of interview. Of the households that were found, 98 percent were successfully interviewed.
In these households, 8,652 women were identified as eligible for the individual interview. Interviews were completed with 98 percent of the women. Of the 2,717 eligible men identified, 94 percent were successfully interviewed.
Note: See summarized response rates by residence (urban/rural) in Table 1.1 of the Final Report.
The estimates from a sample survey are affected by two types of errors: nonsampling errors and 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
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TwitterVeteran Employment Outcomes (VEO) are new experimental U.S. Census Bureau statistics on labor market outcomes for recently discharged Army veterans. These statistics are tabulated by military specialization, service characteristics, employer industry (if employed), and veteran demographics. They are generated by matching service member information with a national database of jobs, using state-of-the-art confidentiality protection mechanisms to protect the underlying data.
https://lehd.ces.census.gov/data/veo_experimental.html
"The VEO are made possible through data sharing partnerships between the U.S. Army, State Labor Market Information offices, and the U.S. Census Bureau. VEO data are currently available at the state and national level."
"Veteran Employment Outcomes (VEO) are experimental tabulations developed by the Longitudinal Employer-Household Dynamics (LEHD) program in collaboration with the U.S. Army and state agencies. VEO data provides earnings and employment outcomes for Army veterans by rank and military occupation, as well as veteran and employer characteristics. VEO are currently released as a research data product in "experimental" form."
"The source of veteran information in the VEO is administrative record data from the Department of the Army, Office of Economic and Manpower Analysis. This personnel data contains fields on service member characteristics, such as service start and end dates, occupation, pay grade, characteristics at entry (e.g. education and test scores), and demographic characteristics (e.g. sex, race, and ethnicity). Once service member records are transferred to the Census Bureau, personally-identifying information is stripped and veterans are assigned a Protected Identification Key (PIK) that allows for them to be matched with their employment outcomes in Census Bureau jobs data."
Earnings, and Employment Concepts
Earnings "Earnings are total annual earnings for attached workers from all jobs, converted to 2018 dollars using the CPI-U. For the annual earnings tabulations, we impose two labor force attachment restrictions. First, we drop veterans who earn less than the annual equivalent of full-time work at the prevailing federal minimum wage. Additionally, we drop veterans with two or more quarters with no earnings in the reference year. These workers are likely to be either marginally attached to the labor force or employed in non-covered employment."
Employment
"While most VEO tabulations include earnings from all jobs, tabulations by employer characteristics only consider the veteran's main job for that year. Main jobs are defined as the job for which veterans had the highest earnings in the reference year. To attach employer characteristics to that job, we assign industry and geography from the highest earnings quarter with that employer in the year. For multi-establishment firms, we use LEHD unit-to-worker imputations to assign workers to establishments, and then assign industry and geography."
https://lehd.ces.census.gov/data/veo_experimental.html
United States Census Bureau
https://lehd.ces.census.gov/data/veo_experimental.html
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U.S. Veterans.
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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 110th Congressional District Summary File (Sample) (110CDSAMPLE) contains the sample data, which is the information compiled from the questions asked of a sample of all people and housing units. Population items include basic population totals; urban and rural; households and families; marital status; grandparents as caregivers; language and ability to speak English; ancestry; place of birth, citizenship status, and year of entry; migration; place of work; journey to work (commuting); school enrollment and educational attainment; veteran status; disability; employment status; industry, occupation, and class of worker; income; and poverty status. Housing items include basic housing totals; urban and rural; number of rooms; number of bedrooms; year moved into unit; household size and occupants per room; units in structure; year structure built; heating fuel; telephone service; plumbing and kitchen facilities; vehicles available; value of home; monthly rent; and shelter costs. The file contains subject content identical to that shown in Summary File 3 (SF 3).
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TwitterThis page contains results of recent projections produced by the GLA that have been designated as research outputs rather than as a full entry in the GLA's annual series of projections. Update - 6 August 2025 Initial 2024-based trend projection outputs have been added. For more information, please see this blog post. The decision not to give a full release to the 2023-based projections was a consequence of problems with official population estimates used as inputs to the models; they are set to be updated later in 2025 once updated estimates are released by ONS. These outputs were produced in April 2025 as part of the population and pupil projection services that the GLA offers to local authorities in London and are presented here to: · Indicate the potential scale of impacts that recent updates and revisions to Long-Term International Migration (LTIM) estimates for the UK may have on the final projections. · Demonstrate the results of a newly introduced methodology for projecting future fertility rates. · Provide users an opportunity to give feedback on the updated set of projection variants being considered for inclusion in future releases. · Be used as model inputs during the development of the GLA’s upcoming household projections. A note providing an overview of the results of and background to these projections will be added in the coming weeks. The GLA's 2022-based population projections are available here.
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According to our latest research, the global CT scanners market size in 2024 stands at USD 7.8 billion, demonstrating robust growth driven by technological advancements and increasing demand for advanced diagnostic imaging. The market is expected to expand at a CAGR of 5.4% from 2025 to 2033, reaching a projected value of USD 12.7 billion by 2033. This impressive growth trajectory is primarily fueled by the rising prevalence of chronic diseases, growing geriatric populations, and the continuous integration of artificial intelligence and machine learning in medical imaging solutions, which are transforming diagnostic accuracy and patient outcomes across the globe.
One of the primary growth factors propelling the CT scanners market is the escalating incidence of chronic conditions such as cancer, cardiovascular diseases, and neurological disorders. As these ailments require early and precise diagnosis for effective treatment, healthcare facilities are increasingly investing in advanced CT imaging technologies. The ability of CT scanners to provide high-resolution, three-dimensional images in a non-invasive manner makes them indispensable for clinicians seeking to detect, monitor, and manage complex medical conditions. Furthermore, the ongoing shift towards minimally invasive diagnostic procedures is boosting the adoption of CT scanners, as they offer rapid and accurate visualization of internal structures with minimal patient discomfort.
Technological innovation is another significant driver shaping the CT scanners market landscape. The development of high-slice and spectral CT scanners has markedly improved image quality, scanning speed, and diagnostic confidence, particularly in challenging clinical scenarios. Integration of artificial intelligence and deep learning algorithms has further enhanced the utility of CT scanners by automating image interpretation, reducing human error, and enabling personalized imaging protocols. Additionally, the advent of low-dose CT technology is addressing concerns related to radiation exposure, making CT imaging safer and more accessible for a broader patient demographic, including pediatric and repeat patients.
Government initiatives and favorable reimbursement policies are also playing a pivotal role in expanding the CT scanners market. In many developed and emerging economies, public and private healthcare providers are increasing investments in medical infrastructure, prioritizing the procurement of advanced imaging equipment to improve diagnostic capabilities. Regulatory agencies are streamlining approval pathways for innovative CT technologies, facilitating faster market entry and adoption. Simultaneously, the growing demand for point-of-care diagnostics and the expansion of healthcare services into rural and underserved areas are creating new opportunities for market players, particularly in emerging markets where healthcare access is rapidly improving.
From a regional perspective, North America continues to dominate the CT scanners market, accounting for the largest share in 2024, followed closely by Europe and the Asia Pacific. The high adoption rate of advanced medical technologies, well-established healthcare infrastructure, and significant investments in research and development are key contributors to North America's leadership position. Meanwhile, the Asia Pacific region is witnessing the fastest growth, fueled by rising healthcare expenditure, increasing awareness about early disease detection, and the rapid expansion of private healthcare facilities. Latin America and the Middle East & Africa are also exhibiting steady growth, albeit from a smaller base, as governments prioritize healthcare modernization and diagnostic imaging accessibility.
The CT scanners market is segmented by product type into Low-Slice CT Scanners, Medium-Slice CT Scanners, and High-Slice CT Scanners, each catering to distinct clinical requirements and healthcare settings. Low-slic
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TwitterThis is a MD iMAP hosted service. Find more information at http://imap.maryland.gov. The American Community Survey (ACS) is a nationwide - continuous survey designed to provide communities with reliable and timely demographic - housing - social and economic data. The ACS replaces the decennial census long form in 2010 and every year thereafter. The annual ACS sample is smaller than that of previous long form surveys resulting in a larger sampling error. Coefficients of Variation (CVs) - which are statistical measures that show the relative amount of sampling error associated with an estimate - are presented here as a measure of reliability and usability of the data. The unit of geography used for the 2010 - 2014 data is the census tract - a small statistical area within a county - which is delineated every 10 years prior to the decennial census.Feature Service Link:https://mdgeodata.md.gov/imap/rest/services/Demographics/MD_AmericanCommunitySurvey/FeatureServer ADDITIONAL LICENSE TERMS: The Spatial Data and the information therein (collectively "the Data") is provided "as is" without warranty of any kind either expressed implied or statutory. The user assumes the entire risk as to quality and performance of the Data. No guarantee of accuracy is granted nor is any responsibility for reliance thereon assumed. In no event shall the State of Maryland be liable for direct indirect incidental consequential or special damages of any kind. The State of Maryland does not accept liability for any damages or misrepresentation caused by inaccuracies in the Data or as a result to changes to the Data nor is there responsibility assumed to maintain the Data in any manner or form. The Data can be freely distributed as long as the metadata entry is not modified or deleted. Any data derived from the Data must acknowledge the State of Maryland in the metadata.
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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 2010 Armenia Demographic and Health Survey (2010 ADHS) is the third in a series of nationally representative sample surveys designed to provide information on population and health issues. It is conducted in Armenia under the worldwide Demographic and Health Surveys program. Specifically, the 2010 ADHS has a primary objective of providing current and reliable information on fertility levels, marriage, sexual activity, fertility preferences, awareness and use of family planning methods, breastfeeding practices, nutritional status of young children, childhood mortality, maternal and child health, and awareness and behavior regarding AIDS and other sexually transmitted infections (STIs). The survey obtained detailed information on these issues from women of reproductive age and, for certain topics, from men as well.
The 2010 ADHS results are intended to provide information needed to evaluate existing social programs and to design new strategies to improve health of and health services for the people of Armenia. Data are presented by region (marz) wherever sample size permits. The information collected in the 2010 ADHS will provide updated estimates of basic demographic and health indicators covered in the 2000 and 2005 surveys.
The long-term objective of the survey includes strengthening the technical capacity of major government institutions, including the NSS. The 2010 ADHS also provides comparable data for longterm trend analysis in Armenia because the 2000, 2005, and 2010 surveys were implemented by the same organisation and used similar data collection procedures. It also adds to the international database of demographic and health–related information for research purposes.
The 2010 ADHS was conducted by the National Statistical Service (NSS) and the MOH of Armenia from October 5 through December 25, 2010.
Sample survey data
The sample was designed to permit detailed analysis-including the estimation of rates of fertility, infant/child mortality, and abortion-at the national level, for Yerevan, and for total urban and total rural areas separately. Many indicators can also be estimated at the regional (marz) level.
A representative probability sample of 7,580 households was selected for the 2010 ADHS sample. The sample was selected in two stages. In the first stage, 308 clusters were selected from a list of enumeration areas in a subsample of a master sample derived from the 2001 Population Census frame. In the second stage, a complete listing of households was carried out in each selected cluster. Households were then systematically selected for participation in the survey.
All women age 15-49 who were either permanent residents of the households in the 2010 ADHS sample or visitors present in the household on the night before the survey were eligible to be interviewed. Interviews were completed with 5,922 women. In addition, in a subsample of one-third of all of the households selected for the survey, all men age 15-49 were eligible to be interviewed if they were either permanent residents or visitors present in the household on the night before the survey. Interviews were completed with 1,584 men.
Appendix A of the Final Report provides additional information on the sample design of the 2010 Armenia DHS.
Face-to-face [f2f]
Three questionnaires were used in the ADHS: a Household Questionnaire, a Woman’s Questionnaire, and a Man’s Questionnaire. The Household Questionnaire and the individual questionnaires were based on model survey instruments developed in the MEASURE DHS program and questionnaires used in the previous 2005 ADHS. The model questionnaires were adapted for use by NSS and MOH. Suggestions were also sought from a number of nongovernmental organizations (NGOs). The questionnaires were developed in English and translated into Armenian. They were pretested in July 2010.
The Household Questionnaire was used to list all usual members of and visitors to the selected households and to collect information on the socioeconomic status of the household. The first part of the Household Questionnaire collected for each household member or visitor information on their age, sex, educational attainment, and relationship to the head of household. This information provided basic demographic data for Armenian households. It also was used to identify the women and men who were eligible for an individual interview (i.e., women and men age 15-49). In the second part of the Household Questionnaire, there were questions on housing characteristics (e.g., the flooring material, the source of water, and the type of toilet facilities), on ownership of a variety of consumer goods, and on other aspects of the socioeconomic status of the household. In addition, the Household Questionnaire was used to obtain information on each child’s birth registration, ask questions about child discipline and child labor, and record height and weight measurements of children under age 5.
The Woman’s Questionnaire obtained information from women age 15-49 on the following topics: - Background characteristics - Pregnancy history - Antenatal, delivery, and postnatal care - Knowledge, attitudes, and use of contraception - Reproductive and adult health - Childhood mortality - Health and health care utilization - Vaccinations of children under age 5 - Episodes of diarrhea and respiratory illness of children under age 5 - Breastfeeding and weaning practices - Marriage and recent sexual activity - Fertility preferences - Knowledge of and attitudes toward AIDS and other sexually transmitted diseases - Woman’s work and husband’s background characteristics
The Man’s Questionnaire, administered to men age 15-49, focused on the following topics: - Background characteristics - Health and health care utilization - Marriage and recent sexual activity - Attitudes toward and use of condoms - Knowledge of and attitudes toward AIDS and other sexually transmitted diseases - Attitudes toward women’s status
Data Processing
The processing of the ADHS results began shortly after fieldwork commenced. Completed questionnaires were returned regularly from the field to NSS headquarters in Yerevan, where they were entered and edited by data processing personnel who were specially trained for this task. The data processing personnel included a supervisor, a questionnaire administrator (who ensured that the expected number of questionnaires from all clusters was received), several office editors, 12 data entry operators, and a secondary editor. The concurrent processing of the data was an advantage because the senior DHS technical staff were able to advise field teams of problems detected during the data entry. In particular, tables were generated to check various data quality parameters. As a result, specific feedback was given to the teams to improve performance. The data entry and editing phase of the survey was completed in March 2011.
A total of 7,580 households were selected in the sample, of which 7,043 were occupied at the time of the fieldwork. The main reason for the difference is that some of the dwelling units that were occupied during the household listing operation were either vacant or the household was away for an extended period at the time of interviewing. The number of occupied households successfully interviewed was 6,700, yielding a household response rate of 95 percent. The household response rate in urban areas (94 percent) was slightly lower than in rural areas (97 percent).
In these households, a total of 6,059 eligible women were identified; interviews were completed with 5,922 of these women, yielding a response rate of 98 percent. In one-third of the households, a total of 1,641 eligible men were identified, and interviews were completed with 1,584 of these men, yielding a response rate of 97 percent. Response rates are slightly lower in urban areas (97 percent for women and 96 percent for men) than in rural areas where rates were 99 and 97 percent, respectively.
Detailed information on sampling errors is provided in Appendix B of the Final Report.
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TwitterThe survey provides comprehensive information on demographic characteristics, Migration, Health, Housing and Access to Basic Amenities and Cultural Aspects. Demographic information has been collected to cross classify variables of other section viz migration, health etc; by demographic characteristics of the population.
Information on internal migration was one of the subjects which has been covered in this survey. In addition to fertility and mortality, the third factor affecting population change in a given area is migration. The movement of population from one area to another affects its age, sex composition and geographical distribution:. This movement of population within the national boundaries of a country is called the internal migration and the movement across the national boundaries is called the international migration. This survey provide information on long term, medium term as well as short term migration.
Information on health status of its population and utilization of health services is a basic requirement for planning and evaluation of health services in the country and for monitoring the health status of the population. This survey gathered information on health such as age, sex, distribution of these patients, their household income, employment, household size and composition, their housing conditions, sources of water for drinking, toilet facilities available for them etc. which generally cannot be obtained through service statistics. Information on Housing and Access to Basic Amenities were also collected in this survey. Detailed information on housing, which are very essential for planning and policy formulation in this area were collected through this survey. Information on Cultural and Recreational activities were also collected at this survey such as usage of cinemas, theatres and libraries, participation in cultural events etc.
National coverage.
Household, Individuals
Housing units representing all the disitricts & sectors of the country
Sample survey data [ssd]
A sample of 25,000 housing units, representing all the districts and sectors of the country was selected for the survey to give estimates at district level. The sample was spread over a period of 12 months to cover the seasonal fluctuations of some variables collected in the survey.
Face-to-face [f2f]
Data entry checks· Range checks and a number of other simple edit checks were performed on the data entry machines (key to disk) while the data was being keyed.
Computer edits Most of the edits performed manually were incorporated in the computer edits and the data was thoroughly cleaned before the working master fl1es were created. The computer edit consists of three parts. (i) Structural edit (ii) Range edit (iii) Consistency checks within sections and between sections
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Emergency medical services (EMS) workforce demographics in the United States do not reflect the diversity of the population served. Despite some efforts by professional organizations to create a more representative workforce, little has changed in the last decade. This scoping review aims to summarize existing literature on the demographic composition, recruitment, retention, and workplace experience of underrepresented groups within EMS. Peer-reviewed studies were obtained from a search of PubMed, CINAHL, Web of Science, ProQuest Thesis and Dissertations, and non-peer-reviewed (“gray”) literature from 1960 to present. Abstracts and included full-text articles were screened by two independent reviewers trained on inclusion/exclusion criteria. Studies were included if they pertained to the demographics, training, hiring, retention, promotion, compensation, or workplace experience of underrepresented groups in United States EMS by race, ethnicity, sexual orientation, or gender. Studies of non-EMS fire department activities were excluded. Disputes were resolved by two authors. A single reviewer screened the gray literature. Data extraction was performed using a standardized electronic form. Results were summarized qualitatively. We identified 87 relevant full-text articles from the peer-reviewed literature and 250 items of gray literature. Primary themes emerging from peer-reviewed literature included workplace experience (n = 48), demographics (n = 12), workforce entry and exit (n = 8), education and testing (n = 7), compensation and benefits (n = 5), and leadership, mentorship, and promotion (n = 4). Most articles focused on sex/gender comparisons (65/87, 75%), followed by race/ethnicity comparisons (42/87, 48%). Few articles examined sexual orientation (3/87, 3%). One study focused on telecommunicators and three included EMS physicians. Most studies (n = 60, 69%) were published in the last decade. In the gray literature, media articles (216/250, 86%) demonstrated significant industry discourse surrounding these primary themes. Existing EMS workforce research demonstrates continued underrepresentation of women and nonwhite personnel. Additionally, these studies raise concerns for pervasive negative workplace experiences including sexual harassment and factors that negatively affect recruitment and retention, including bias in candidate testing, a gender pay gap, and unequal promotion opportunities. Additional research is needed to elucidate recruitment and retention program efficacy, the demographic composition of EMS leadership, and the prevalence of racial harassment and discrimination in this workforce.