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The China Multi-Generational Panel Dataset - Liaoning (CMGPD-LN) is drawn from the population registers compiled by the Imperial Household Agency (neiwufu) in Shengjing, currently the northeast Chinese province of Liaoning, between 1749 and 1909. It provides 1.5 million triennial observations of more than 260,000 residents from 698 communities. The population mainly consists of immigrants from North China who settled in rural Liaoning during the early eighteenth century, and their descendants. The data provide socioeconomic, demographic, and other characteristics for individuals, households, and communities, and record demographic outcomes such as marriage, fertility, and mortality. The data also record specific disabilities for a subset of adult males. Additionally, the collection includes monthly and annual grain price data, custom records for the city of Yingkou, as well as information regarding natural disasters, such as floods, droughts, and earthquakes. This dataset is unique among publicly available population databases because of its time span, volume, detail, and completeness of recording, and because it provides longitudinal data not just on individuals, but on their households, descent groups, and communities.

The China Multi-Generational Panel Dataset - Shuangcheng (CMGPD-SC) provides longitudinal individual, household, and community information on the demographic and socioeconomic characteristics of a resettled population living in Shuangcheng, a county in present-day Heilongjiang Province of Northeastern China, for the period from 1866 to 1913. The dataset includes some 1.3 million annual observations of over 100,000 unique individuals descended from families who were relocated to Shuangcheng in the early 19th century. These families were divided into 3 categories based on their place of origin: metropolitan bannermen, rural bannermen, and floating bannermen. The CMGPD-SC, like its Liaoning counterpart, the CMGPD-LN (ICPSR 27063), is a valuable data source for studying longitudinal as well as multi-generational social and demographic processes. The population categories had salient differences in social origins and land entitlements, and landholding data are available at a number of time periods, thus the CMGPD-SC is especially suitable to the study of stratification processes.

This study contains selected demographic, social, economic, public policy, and political comparative data for Switzerland, Canada, France, and Mexico for the decades of 1900-1960. Each dataset presents comparable data at the province or district level for each decade in the period. Various derived measures, such as percentages, ratios, and indices, constitute the bulk of these datasets. Data for Switzerland contain information for all cantons for each decennial year from 1900 to 1960. Variables describe population characteristics, such as the age of men and women, county and commune of origin, ratio of foreigners to Swiss, percentage of the population from other countries such as Germany, Austria and Lichtenstein, Italy, and France, the percentage of the population that were Protestants, Catholics, and Jews, births, deaths, infant mortality rates, persons per household, population density, the percentage of urban and agricultural population, marital status, marriages, divorces, professions, factory workers, and primary, secondary, and university students. Economic variables provide information on the number of corporations, factory workers, economic status, cultivated land, taxation and tax revenues, canton revenues and expenditures, federal subsidies, bankruptcies, bank account deposits, and taxable assets. Additional variables provide political information, such as national referenda returns, party votes cast in National Council elections, and seats in the cantonal legislature held by political groups such as the Peasants, Socialists, Democrats, Catholics, Radicals, and others. Data for Canada provide information for all provinces for the decades 1900-1960 on population characteristics, such as national origin, the net internal migration per 1,000 of native population, population density per square mile, the percentage of owner-occupied dwellings, the percentage of urban population, the percentage of change in population from preceding censuses, the percentage of illiterate population aged 5 years and older, and the median years of schooling. Economic variables provide information on per capita personal income, total provincial revenue and expenditure per capita, the percentage of the labor force employed in manufacturing and in agriculture, the average number of employees per manufacturing establishment, assessed value of real property per capita, the average number of acres per farm, highway and rural road mileage, transportation and communication, the number of telephones per 100 population, and the number of motor vehicles registered per 1,000 population. Additional variables on elections and votes are supplied as well. Data for France provide information for all departements for all legislative elections since 1936, the two presidential elections of 1965 and 1969, and several referenda held in the period since 1958. Social and economic data are provided for the years 1946, 1954, and 1962, while various policy data are presented for the period 1959-1962. Variables provide information on population characteristics, such as the percentages of population by age group, foreign-born, bachelors aged 20 to 59, divorced men aged 25 and older, elementary school students in private schools, elementary school students per million population from 1966 to 1967, the number of persons in household in 1962, infant mortality rates per million births, and the number of priests per 10,000 population in 1946. Economic variables focus on the Gross Nat,ional Product (GNP), the revenue per capita per household, personal income per capita, income tax, the percentage of active population in industry, construction and public works, transportation, hotels, public administration, and other jobs, the percentage of skilled and unskilled industrial workers, the number of doctors per 10,000 population, the number of agricultural cooperatives in 1946, the average hectares per farm, the percentage of farms cultivated by the owner, tenants, and sharecroppers, the number of workhorses, cows, and oxen per 100 hectares of farmland in 1946, and the percentages of automobiles per 1,000 population, radios per 100 homes, and cinema seats per 1,000 population. Data are also provided on the percentage of Communists (PCF), Socialists, Radical Socialists, Conservatives, Gaullists, Moderates, Poujadists, Independents, Turnouts, and other political groups and parties in elections 1946-1969. Additional variables provide information on medical insurance, death benefits, and aid to families. Data for Mexico provide information for all states at decennial points from 1910 to 1960. Social and economic data are available for the entire period, while political and public policy data are presented for the decades beginning with 1930. Variables are provided on population size, population density per kilogram, the percentage of illiterate population, the percentage increase in population by decade, the percentage of economically active population, the total per capita state revenues and expenditures, per capita personal income, median family income, minimum salary in city and in countryside, the poverty index in percentages, the average number of employees per industrial firm, the average investment per manufacturing establishment, the value of industrial and agricultural products in pesos per capita, the average number of hectares per farm, gasoline consumption in litres per capita, and the number of telephones and of registered motor vehicles per 1,000 population. Variables also provide information on the percentage of registered voters who voted in elections.

The Eurobarometer series is a unique cross-national and cross-temporal survey program conducted on behalf of the European Commission. These surveys regularly monitor public opinion in the European Union (EU) member countries and consist of standard modules and special topic modules. The standard modules address attitudes towards European unification, institutions and policies, measurements for general socio-political orientations, as well as respondent and household demographics. The special topic modules address such topics as agriculture, education, natural environment and resources, public health, public safety and crime, and science and technology. This round of Eurobarometer surveys covers the following special topics: (1) E-Communications and the Digital Single Market, (2) Awareness and Perceptions of Europeans about EU Customs, and (3) EU Citizens, Agriculture, and the Common Agricultural Policy. Respondents were queried as to their use of telephones and digital electronics, the importance of specific factors in choosing to subscribe to an Internet connection, paid services that can be accessed via the Internet, bundling Internet connection with other services, and switching communication service providers. Questions were also asked regarding respondents' perceptions of EU customs authorities and their activities, the role of EU customs authorities, and how informed respondents were about various aspects of the EU Customs Union. Additional topics included respondents' support of the Common Agricultural Policy (CAP), the primary responsibilities of EU farmers, the effectiveness of the CAP, approval of EU financial support of the CAP, and importance of environmental protection. Demographic and other background information collected includes age, gender, nationality, marital status, occupation, political preference, age when stopped full-time education, household composition, ownership of a fixed or mobile telephone and other goods, difficulties in paying bills, level in society, and Internet use. In addition, country-specific data includes type and size of locality, region of residence, and language of interview.

The purpose of this project is to study the early development of a group of children who are at risk regarding later successful adjustment and for whom we have little information: children living in rural, largely poor communities. A birth cohort of 800 children in three rural counties of North Carolina and 600 children in three rural counties of Pennsylvania were studied over the first 3 years of life. A multidisciplinary team investigated multiple levels of influences affecting the early development of these children. The research emphases of the component research projects include the following: Project I: Temperament: Emphasizes the development of child-related factors and how they predict preschool social-emotional and cognitive competence Project II: School Readiness: Emphasizes the pathways to and precursors of school readiness Project III: Family Process: Emphasizes how family processes mediate or moderate the effects of rural poverty on children Project IV: Work and Family: Emphasizes the impact of parents' occupational conditions on parenting, and, in turn, children's social, cognitive, emotional and linguistic development Project V: Ethnography: Emphasizes two components: an in-depth contextual appraisal of community characteristics a family ethnography with 72 families developmentally ahead of the cohort above to provide input to design and measurement This project used a cumulative risk model to examine the relation between social risk and children's executive functioning, language development and behavioral competence at 36 months. Using both the Family Process Model of development and the Family Investment Model of development, observed parenting was examined over time in relation to child functioning at 36 months. Different aspects of observed parenting were examined as mediators/moderators of risk in predicting child outcomes. Results suggested that cumulative risk was important in predicting all three major domains of child outcomes and that positive and negative parenting and maternal language complexity were mediators of these relations. Maternal positive parenting was found to be a buffer for the most risky families in predicting behavioral competence. In a final model using both family process and investment measures, there was evidence of mediation but with little evidence of the specificity of parenting for particular outcomes. Results demonstrate the importance of cumulative risk and parenting in understanding child competence in rural poverty and the implications for possible intervention strategies that might be effective in maximizing the early development of these children.

The Longitudinal Study of Older People in Anhui Province, China, 2001-2003 examined the physical and psychological well-being of older adults (aged 60 and above) living in rural Anhui Province, China. The original purpose of the study was to study the impact of rural-to-urban migration on the physical and psychological well-being of older adults left behind in rural villages by their adult children. This collection contains two parts; Part 1: 2001 Survey and Part 2: 2003 Follow-up Survey. Similar Questions were asked in the two surveys to assess intergenerational transfers and relations of the respondents, including social support, caregiving, emotional cohesion, remittances, grandchild care, and filial piety. Respondents were also asked about their health status (physical, emotional, and cognitive). Demographic information includes age, sex, marriage status, and education.

The Mekong Island Population Laboratory (MIPopLab) conducted 13 rounds of data collection between 2000 and 2006, at which point MIPopLab was integrated into the Mekong Integrated Population-Registration Areas of Cambodia (MIPRAoC). MIPopLab combined a demographic surveillance system in one rural area of Cambodia with a population of roughly 10,000 inhabitants and a "rider survey" designed to assess the role of the late-1970s mortality crisis in subsequent fertility changes. At the time of registration (first household visit), complete marriage and birth histories were recorded for all eligible women, i.e., women between the ages of 15 and 74. MIPopLab was thus set up to provide both retrospective data on reproductive behavior and prospective follow-up data on population dynamics.

Rural-urban classifications are essential for analyzing geographic, demographic, environmental, and social processes across the rural-urban continuum. Most existing classifications are, however, only available at relatively aggregated spatial scales, such as at the county scale in the United States. The absence of rurality or urbanness measures at high spatial resolution poses significant problems when the process of interest is highly localized, as with the incorporation of rural towns and villages into encroaching metropolitan areas. Moreover, existing rural-urban classifications are often inconsistent over time, or require complex, multi-source input data (e.g., remote sensing observations or road network data), thus, prohibiting the longitudinal analysis of rural-urban dynamics. We developed a set of distance- and spatial-network-based methods for consistently estimating the remoteness and rurality of places at fine spatial resolution, over long periods of time. Based on these methods, we constructed indices of urbanness for 30,000 places in the United States from 1930 to 2018. We call these indices the place-level urban-rural index (PLURAL), enabling long-term, fine-grained analyses of urban and rural change in the United States.

For this study of political systems performance in Sweden, time-series annual data were compiled for the period 1865-1967. Variables provide information on population characteristics, such as the total population, the number of people aged 0 to 14 years, 0 to 4 years, and over 65, birth rate, live births per 1,000 population, infant mortality rate, gross death rate, and life expectancy at birth for females, the number of elementary school students, secondary school students, and university students, the number of civil servants, doctors, midwives, hospital beds, school teachers, and university teachers, the population of the three largest cities, and the urban population. Economic variables provide information on government revenues, government expenditures on defense, education, pensions, welfare, public health, veterans' benefits, and labor benefits, Gross National Product (GNP), percentage of the population employed in agriculture, the value of agricultural production, energy consumption, the maximum income tax rate, the number of recipients of public relief, the number of recipients of public pensions, unemployment rate, price index, and the number of union members. Other variables provide information on the enfranchised population, voting turnout, votes for parties of the Left, and the number of suicides.

This study addressed whether it is better to expand the scope of collaborative care programs to treat patients with more complex psychiatric disorders or to facilitate successful referrals to specialty mental health care. The primary objective of this study is to compare Telepsychiatry Collaborative Care (TCC) and Telepsychiatry Enhanced Referral (TER) from the patient and provider perspective. The secondary objective is to determine whether patients not engaging and responding to TER, improve with Phone-Psychiatry Enhanced Referral (PER). There are four specific aims. Aim #1: To quantitatively compare the treatment experience, engagement, self-reported clinical outcomes, and recovery-oriented outcomes of patients initially randomized to TCC and TER. Aim #2: For the subset of patients randomized to TER who do not engage in treatment and are still symptomatic at 6 months, quantitatively compare treatment experience, treatment engagement, self-reported clinical outcomes and recovery-oriented outcomes of patients randomized to continued-TER or PER. Aim #3: To gain an in-depth understanding of patients' and providers' treatment experience, qualitatively compare those randomized to TCC, TER and PER. Aim #4: To examine treatment heterogeneity among subgroups of patients randomized to TCC and TER based on race/ethnicity, age and clinical severity.