Primary and secondary data summary for systematic review titled "Medical therapies for pediatric lymphatic malformations: a systematic review"

Secondary data linkage plan for primary and secondary outcomes.

Large-scale emergencies, like the ongoing COVID-19 pandemic, demonstrate pervasive effects across multiple sectors. There is a continually growing body of evidence demonstrating gender and sex differences in COVID-19 disease, as well as its health, social, and economic impacts. While online resources have worked to compile this evidence, there is a need to evaluate and synthesize the available gender- and sex-disaggregated data related to COVID-19. This literature review will systematically assess and compile current literature and evidence from different disciplines. We will include peer reviewed articles, clinical studies and reports, and relevant working papers using secondary data analyses and primary research methodologies. We will synthesize and describe the evidence on multiple outcomes of interest, including gender and sex differences in mortality, severity, treatment outcomes, exposure to violence, mental health and psychosocial support needs, and economic insecurity with COVID-19. These results can be used to inform policy, identify research gaps, and support recommendations for priority interventions.

Actual value and historical data chart for Myanmar Gross Enrolment Ratio Primary And Secondary Male Percent

International students’ mental health has become an increasing concern in recent years, as more students leave their country for better education. They experience a wide range of challenges while studying abroad that have an impact on their psychological well-being. These challenges can include language obstacles, cultural differences, homesickness, financial issues and other elements that could severely impact the mental health of international students. Given the limited research on the demographic, cultural, and psychosocial variables that influence international students’ mental health, and the scarcity of studies on the use of machine learning algorithms in this area, this study aimed to analyse data to understand the demographic, cultural factors, and psychosocial factors that impact mental health of international students. Additionally, this paper aimed to build a machine learning-based model for predicting depression among international students in the United Kingdom. This study utilized both primary data gathered through an online survey questionnaire targeted at international students and secondary data was sourced from the ’A Dataset of Students’ Mental Health and Help-Seeking Behaviors in a Multicultural Environment,’ focusing exclusively on international student data within this dataset. We conducted data analysis on the primary data and constructed models using the secondary data for predicting depression among international students. The secondary dataset is divided into training (70%) and testing (30%) sets for analysis, employing four machine learning models: Logistic Regression, Decision Tree, Random Forest, and K Nearest Neighbor. To assess each algorithm’s performance, we considered metrics such as Accuracy, Sensitivity, Specificity, Precision and AU-ROC curve. This study identifies significant demographic variables (e.g., loan status, gender, age, marital status) and psychosocial factors (financial difficulties, academic stress, homesickness, loneliness) contributing to international students’ mental health. Among the machine learning models, the Random Forest model demonstrated the highest accuracy, achieving an 80% accuracy rate in predicting depression.

School enrollment, primary and secondary (gross), gender parity index (GPI) in Chad was reported at 0.7524 % in 2021, according to the World Bank collection of development indicators, compiled from officially recognized sources. Chad - Ratio of girls to boys in primary and secondary education - actual values, historical data, forecasts and projections were sourced from the World Bank on October of 2025.

This collection contains measures of primary and secondary roads (highways and main arteries) per United States census tract and per United States ZIP code tabulation area (ZCTA) in 2010 and 2020. These measures may be used as a proxy for heavy traffic, high traffic speeds, and impediments to walking or biking. Variables include: counts of primary, secondary, and all streets per tract and per ZCTA; total length of primary, secondary, and all streets per tract and per ZCTA; ratio of primary and/or secondary road counts to all roads; and ratio of length of primary/secondary roads to all streets.

This dataset is a compilation and synthesis of secondary data in South Florida (Martin, Palm Beach, Broward, Miami-Dade, and Monroe Counties) corresponding to the following topics: Human population changes near coral reefs, Economic impact of coral reef fishing to jurisdiction, Economic impact of dive/snorkel tourism to jurisdiction, Community well-being, Physical infrastructure, and Governance. Data are collected from a variety of publicly available sources to supplement primary data collected through resident surveys. These secondary data are collected to address topics outside the scope of NCRMP resident surveys, and are collected on an annual basis throughout the US coral reef jurisdictions. The primary data that were collected as part of this study in Florida are available in NCEI Accession 0161541.

Students can explore some of the Library of Virginia’s collections and learn how they are conserved! The Library of Virginia is the oldest cultural institution in the state and the official archive (a place where history is kept) and library of the Commonwealth. In the book To Collect, Protect, and Serve: Behind the Scenes at the Library of Virginia, Archie the Archivist, Libby the Librarian, and Connie the Conservator guide young readers through a visit to the Library of Virginia. Check out these To Collect, Protect, and Serve worksheet activities.

Overview of the parameters of primary data generation.

This dataset is a compilation and synthesis of secondary data in Hawaii corresponding to the following topics: Human population changes near coral reefs, Economic impact of coral reef fishing to jurisdiction, Economic impact of dive/snorkel tourism to jurisdiction, Community well-being, Physical infrastructure, and Governance. Data are collected from a variety of publicly available sources to supplement primary data collected through resident surveys. These secondary data are collected to address topics outside the scope of NCRMP resident surveys, and are collected on an annual basis throughout the US coral reef jurisdictions. The primary data that were collected as part of this study in Hawaii are available in NCEI Accession 0161545.

Description of data–primary, secondary and pooled data.

Health Poverty Index - Situation of Health: Effective primary/secondary care Source: Department of Health (DoH), Hospital Episode Statistics (HES), ONS Mid Year Estimates Publisher: Health Poverty Index Geographies: Local Authority District (LAD), National Geographic coverage: England Time coverage: (Data from different timepoints between 1998 and 2002) Type of data: Administrative data

Detection Rate of Wasting of Primary and Secondary School Students

Primary and secondary outcome measures.

The dataset contains information on, 1. Primary school net attendance ratio (Primary adjusted net attendance ratio)- Number of children attending primary or secondary school who are of official primary school age, expressed as a percentage of the total number of children of official primary school age. 2. Secondary school net attendance ratio (Secondary adjusted net attendance ratio) - Number of children attending secondary or tertiary school who are of official secondary school age, expressed as a percentage of the total number of children of official secondary school age.

Comprehensive dataset containing 10 verified Combined primary and secondary school businesses in Turkey with complete contact information, ratings, reviews, and location data.

This dataset contains records for each public secondary and elementary education agency in the United States and its outlying areas (American Samoa, Guam, Puerto Rico, the Virgin Islands, and the Marshall Islands) for 1985-1986. Reporting agencies serve instructional levels from pre-kindergarten through grade 12, or the equivalent span of instruction in ungraded or special education districts. Regional Educational Service Agencies, supervisory unions, and county superintendents are also represented. Variables include state and federal ID numbers, agency name, address, city, and ZIP code, FIPS county and out-of-state indicators, instructional operating status, agency type, grade span, metropolitan statistical area (MSA) ID and status, and board of control selection code.

Comprehensive dataset containing 56 verified Combined primary and secondary school businesses in Vietnam with complete contact information, ratings, reviews, and location data.