The National Survey of Child and Adolescent Well-Being (NSCAW) is a nationally representative, longitudinal survey of children and families who have been the subjects of investigation by Child Protective Services. There are currently two cohorts of available data (NSCAW I and NSCAW II) drawn from first-hand reports from children, parents, and other caregivers, as well as reports from caseworkers, teachers, and data from administrative records. NSCAW examines child and family well-being outcomes in detail and seeks to relate those outcomes to experience with the child welfare system and to family characteristics, community environment, and other factors. Units of Response: Children and Families in the Child Welfare System Type of Data: Survey Tribal Data: Unavailable Periodicity: Irregular Demographic Indicators: Disability;Ethnicity;Geographic Areas;Household Income;Household Size;Race SORN: Not Applicable Data Use Agreement: https://www.ndacan.acf.hhs.gov/datasets/order_forms/termsofuseagreement.pdf Data Use Agreement Location: https://www.ndacan.acf.hhs.gov/datasets/pdfs_user_guides/IntroNSCAWWave1.pdf Granularity: Individual Spatial: United States Geocoding: Unavailable

Nationally representative, longitudinal data describing functioning of and services for children who are reported to child protective services

This dataset tracks the updates made on the dataset "National Survey of Child and Adolescent Well-Being (NSCAW)" as a repository for previous versions of the data and metadata.

This dataset tracks the updates made on the dataset "National Survey of Child and Adolescent Well-Being" as a repository for previous versions of the data and metadata.

Surveys in other countries suggest that children and adolescents experience high rates of mental health problems, however in Australia there has been no information at a national level about the prevalence of child and adolescent mental health problems. The Child and Adolescent Component of the National Survey of Mental Health and Well-Being is the first survey to investigate the mental health and well-being of children and adolescents at a national level in Australia. It provides an accurate estimate of the prevalence of mental health problems among children and adolescents in Australia. It also provides information about the degree of disability associated with mental health problems and the extent to which children and adolescents are receiving help for their problems. Information was collected from children aged 4-17 and their parents. Children and parents completed questionnaires assessing mental health problems (assessed using the Youth Self-Report and Child Behaviour Checklist) health related quality of life, health-risk behaviour and service utilisation. In addition, parents completed a face-to-face interview (3 modules from the Diagnostic Interview Schedule for Children) designed to identify Depressive Disorder, Attention Deficit/Hyperactivity Disorder and Conduct Disorder. Background variables include age, sex, metro/rural, parents employment/ education/income.

The goal of the Children and Domestic Violence Services (CADVS) was to provide a rich description of the variation in state, county, and local policies and practices related to the issue of co-occurring child maltreatment and domestic violence. The CADVS collected state and local contextual data via telephone interviews with Child Welfare Services (CWS) and Domestic Violence Services (DVS) agencies to provide information on policies and practices for domestic violence and child maltreatment relevant to (1) child placement in out-of-home care, and (2) the use of family preservation services and residential stability among these families in the child welfare system. These contextual data then were linked to the National Survey of Child and Adolescent Well-Being (NSCAW), the parent study and longitudinal survey of youth, parents and other caregivers, child welfare workers, and teachers, which provided indicators needed for child characteristics, caregiver characteristics, child placement career, and mental health services. For this supplement to the NSCAW, a snowball interviewing technique was used. On the front end, CWS agencies were sent an overview letter about the study. Initial contacts were interviewed and, if appropriate, were asked to nominate and facilitate introductions to other contacts to locate the best informant for each interview _domain. Each CWS informant then was asked to provide contact information for the local provider(s) of DVS, including a contact name, if possible. Data from these respondents was used to assess interagency agreement on local policies and practices. Identified DVS representative agencies then received the same introductory letters about the study sent to the CWS agencies. A snowball interviewing technique was again used to identify informants in each agency who would be best able to answer questions regarding related services. The key informants from both the CWS and DVS agencies received additional information on the study, an interview summary, and a copy of the informed consent agreement. Interview data then were collected from CWS and DVS agency informants by telephone. This process began in January 2003 and was completed in February 2004. The need for multiple informants to complete different survey modules for each agency resulted in a total of 860 interviews with 406 interviewees. The data file contains 89 cases and 1,209 variables where each case represents an agency. The measures for CADVS were an amalgamation of (1) child, caregiver and family measures collected in NSCAW and (2) contextual data on policy/practices collected through surveys of states, counties, and localities developed for this particular study. These include such issues as funding, policies regarding the reporting of child maltreatment, referrals made regarding the domestic violence victim or her children, what services are available for children of domestic violence victims, types of service providers, locations of mental and physical health evaluations, and types of training which CWS and DVS staff received.

Spain’s Estudio Nacional de Alimentación en Población Infantil y Adolescente (National Dietary Survey on the Child and Adolescent Population—ENALIA) was designed to estimate the usual intake of energy and nutrients and to gain insight into the dietary habits of children and adolescents (six months - 18 years old). The project forms part of the “EU Menu Project”, a European project coordinated by the European Food Safety Agency (EFSA) and was conducted in accordance with the agreed European methodology guidance.

The "https://addhealth.cpc.unc.edu/" Target="_blank">National Longitudinal Study of Adolescent to Adult Health (Add Health) is a longitudinal study of a nationally representative sample of adolescents in grades 7-12 in the United States during the 1994-95 school year. The Add Health cohort has been followed into young adulthood with four in-home interviews, the most recent in 2008, when the sample was aged 24-32*. Add Health combines longitudinal survey data on respondents' social, economic, psychological and physical well-being with contextual data on the family, neighborhood, community, school, friendships, peer groups, and romantic relationships, providing unique opportunities to study how social environments and behaviors in adolescence are linked to health and achievement outcomes in young adulthood. The fourth wave of interviews expanded the collection of biological data in Add Health to understand the social, behavioral, and biological linkages in health trajectories as the Add Health cohort ages through adulthood. The fifth wave of data collection is planned to begin in 2016.

Initiated in 1994 and supported by three program project grants from the "https://www.nichd.nih.gov/" Target="_blank">Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) with co-funding from 23 other federal agencies and foundations, Add Health is the largest, most comprehensive longitudinal survey of adolescents ever undertaken. Beginning with an in-school questionnaire administered to a nationally representative sample of students in grades 7-12, the study followed up with a series of in-home interviews conducted in 1995, 1996, 2001-02, and 2008. Other sources of data include questionnaires for parents, siblings, fellow students, and school administrators and interviews with romantic partners. Preexisting databases provide information about neighborhoods and communities.

Add Health was developed in response to a mandate from the U.S. Congress to fund a study of adolescent health, and Waves I and II focus on the forces that may influence adolescents' health and risk behaviors, including personal traits, families, friendships, romantic relationships, peer groups, schools, neighborhoods, and communities. As participants have aged into adulthood, however, the scientific goals of the study have expanded and evolved. Wave III, conducted when respondents were between 18 and 26** years old, focuses on how adolescent experiences and behaviors are related to decisions, behavior, and health outcomes in the transition to adulthood. At Wave IV, respondents were ages 24-32* and assuming adult roles and responsibilities. Follow up at Wave IV has enabled researchers to study developmental and health trajectories across the life course of adolescence into adulthood using an integrative approach that combines the social, behavioral, and biomedical sciences in its research objectives, design, data collection, and analysis.

* 52 respondents were 33-34 years old at the time of the Wave IV interview.
** 24 respondents were 27-28 years old at the time of the Wave III interview.

To provide an array of community characteristics by which researchers may investigate the nature of such contextual influences for a wide range of adolescent health behaviors, selected contextual variables have been calculated and compiled. These are provided in this Contextual Database, already linked to the Add Health respondent IDs.

This project examined the problem behaviors of maltreated children and adolescents and the predictors of changes in behavior over an 18-month period. Problem behaviors included aggression, delinquency, risky sexual practices, substance abuse, and suicidal behaviors. The project used data from the National Survey of Child and Adolescent Well-Being (NSCAW), a national probability survey of children assessed following a child maltreatment report. This collection consists of SAS code used to produce subsets of the NSCAW data and the analyses for three chapters of the project's final report. Chapter 2 examined aggression and changes in behavior over 18 months for children aged six to ten years at the time of the baseline interview. Chapter 3 examined self-reported delinquency and caregiver-reported aggressive and delinquent behavior and changes in behavior over 18 months for youth aged 11 to 15 years at the time of the baseline interview. Chapter 4 examined risky behavior changes (risky sexual behavior, substance abuse, and suicidal risk behavior) over 18 months for youth aged 11 to 15 years at the time of the baseline interview.

The National Longitudinal Study of Adolescent to Adult Health (Add Health) Parent Study Public Use collection includes data gathered as part of the Add Health longitudinal survey of adolescents. The original Add Health survey is a longitudinal study of a nationally representative sample of adolescents in grades 7-12 in the United States during the 1994-1995 school year. In Wave 1 of the Add Health Study (1994-1995), a parent of each Add Health Sample Member (AHSM) was interviewed. The Add Health Parent Study gathered social, behavioral, and health survey data in 2015-2017 from the parents of Add Health Sample members who were originally interviewed at Wave 1 (1994-1995). Wave 1 Parents were asked about their adolescent children, their relationships with them, and their own health. The Add Health Parent Study interview is a comprehensive survey of Add Health parents' family relations, education, religious beliefs, physical and mental health, social support, and community involvement experiences. In addition, survey data contains cognitive assessments, a medications log linked to a medications database lookup table, and household financial information collection. The survey also includes permission for administrative data linkages and includes data from a Family Health History Leave-Behind questionnaire. Interviews were conducted with parents' spouse/partner when available. Research domains targeted in the survey and research questions that may be addressed using the Add Health Parent Study data include: Health Behaviors and Risks Many health conditions and behaviors run in families; for example, cardiovascular disease, obesity and substance abuse. How are health risks and behaviors transmitted across generations or clustered within families? How can we use information on the parents' health and health behavior to better understand the determinants of their (adult) children's health trajectories? Cognitive Functioning and Non-Cognitive Personality Traits What role does the intergenerational transmission of personality and locus of control play in generating intergenerational persistence in education, family status, income and health? How do the personality traits of parents and children, and how they interact, influence the extent and quality of intergenerational relationships and the prevalence of assistance across generations? Decision-Making, Expectations, and Risk Preferences Do intergenerational correlations in risk preferences represent intergenerational transmission of preferences? If so, are the transmission mechanisms a factor in biological and environmental vulnerabilities? Does the extent of genetic liability vary in response to both family-specific and generation-specific environmental pressures? Family Support, Relationship Quality and Ties of Obligation How does family complexity affect intergenerational obligations and the strength of relationship ties? As parents near retirement: What roles do they play in their children's lives and their children in their lives? What assistance are they providing to their adult children and grandchildren? What do they receive in return? And how do these ties vary with divorce, remarriage and familial estrangement? Economic Status and Capacities What are the economic capacities of the parents' generation as they reach their retirement years? How have fared through the wealth and employment shocks of the Great Recession? Are parents able to provide for their own financial need? And, do they have the time and financial resources to help support their children and grandchildren and are they prepared to do so?

SUMMARY This table contains data about women, ages 15 to 50, pregnant people, infants, children, and youths, up to age 24. It contains information about a wide range of health topics, including medical conditions, nutrition, dehydration, oral health, mental health, safety, access to health care, and basic needs, like housing. Local, county-level prevalence rates, time trends, and health disparities about national public health priorities, including preterm birth, infant death, childhood obesity, adolescent depression and substance use, and high blood pressure, diabetes, and kidney disease in young adults. The population data is from the 2023-2024 San Francisco Maternal Child and Adolescent Health needs assessment and is published on the Open Data Portal to share with community partners, plan services, and promote health. For more information see: Maternal, Child, and Adolescent Health Homepage Maternal, Child, and Adolescent Health Reports HOW THE DATASET IS CREATED The Maternal, Child, and Adolescent Health (MCAH) Needs Assessment for San Francisco included review of a wide range of citywide population data covering a ten-year span, from 2014 to 2023. Data from over 83,000 birth records, 59,000 death records, 261,000 emergency room visits, 66,000 hospital admissions, and 90,000 newborn screening discharges were gathered, along with citywide data from child welfare records, health screenings in childcare and schools, DMV records of first-time drivers, school surveys, and a state-run mailed survey of recent births (California Department of Public Health MIHA survey). The datasets provided information about approximately 700 health conditions. Each health condition was described in terms of the number of people affected or cases, and the rate affected, stratified by age, sex, race-ethnicity, insurance status, zip code, and time period. Rates were calculated by dividing the number of people or events by the population group estimate (e.g., total births or census estimates), then multiplying by 100 or 1,000 depending on the measure. Each rate was presented with its 95% confidence interval to support users to compare any two rates, either between groups or over time. Two rates differ “significantly” if their 95% confidence intervals do not overlap. The present dataset summarizes the group-level results for any age-, sex-, race-, insurance-, zip code-, and/or period-specific group that included at least 20 people or cases. Causes of death, health conditions that affected over 1000 people in the time frame, problems that got worse over time, and health disparities by insurance, race-ethnicity and/or zip code were flagged for the MCAH Needs Assessment. UPDATE PROCESS The dataset will be updated manually, bi-annually, each December and June. HOW TO USE THIS DATASET Population data from the MCAH needs assessment are shared in several formats, including aggregated datasets on DataSF.gov, downloadable PDF summary reports by age group, interactive online visualizations, data tables, trend graphs, and maps. Information about each variable is available in a linked data dictionary. The definition of each numerator and denominator depends on data source, life stage, and time. Health conditions may not be directly comparable across life stage, if the numerator definition includes age- or pregnancy-specific diagnosis codes (e.g. diabetes hospitalization). For small groups or rare conditions, consider combining time periods and/or groups. Data are suppressed if fewer than 20 cases happened in the group and period. Group-specific rates are available if the matched group-specific census estimates (denominator) were available. Census estim

This report presents findings from the third (wave 3) in a series of follow up reports to the 2017 Mental Health of Children and Young People (MHCYP) survey, conducted in 2022. The sample includes 2,866 of the children and young people who took part in the MHCYP 2017 survey. The mental health of children and young people aged 7 to 24 years living in England in 2022 is examined, as well as their household circumstances, and their experiences of education, employment and services and of life in their families and communities. Comparisons are made with 2017, 2020 (wave 1) and 2021 (wave 2), where possible, to monitor changes over time.

Abstract Objective to examine the problems and challenges facing implementation of policies for Brazilian adolescents, on the basis of narrative review of the findings of the National Survey of School Health (PeNSE). Methods theoretical policy analysis based on narrative review of the three editions of the PeNSE. The articles identified were categorised by priority issues for public policy intervention. Results cigarette smoking held stable, while use of other tobacco products increased by 18%. Regular alcohol use declined from 27.3% (2009) to 23.2% (2015). Drug experimentation increased, while family supervision produced protective effects against tobacco, alcohol and drug use. All indicators of violence increased, including involvement in fights where someone used a firearm or melee weapon. Diet and physical activity displayed predominantly unhealthy habits: (only 20% exercised for an hour or more daily). Sexuality: condom use at first intercourse decreased from 75.9% to 66.2%. Half the students had used a health service in the prior 12 months. Conclusion exposure to risk factors, including alcohol, unsafe sex and violent behaviour and conditions, is high in adolescence, making it important to adopt public policies and inter-sectoral actions that are plural and open to singularity in order to protect the health of adolescents and youth.

The Mental Health of Children and Young People Surveys (MHCYP) series provides data about the mental health of young people living in Great Britain.

The MHCYP was first carried out in 1999, capturing information on 5 to 15-year-olds. It was conducted by the Office for National Statistics (ONS) on behalf of the Department of Health (now known as the Department of Health and Social Care, or DHSC), The Scottish Health Executive and the National Assembly for Wales. The following survey in the series was conducted in 2002 and focused on children looked after by their local authority. The third survey was conducted in 2004 and collected information from 5 to 16-year-olds. Follow-ups to this survey were conducted after 6 months and again after 3 years.

NHS Digital commissioned the 2017 survey on behalf of the DHSC. It collected information on 2 to 19-year-olds living in England. The survey was carried out by a consortium led by NatCen Social Research, which included the ONS and Youth In Mind.

The MHCYP 2020 survey was a Wave 1 follow-up to the 2017 survey and was conducted under the COVID-19 Public Health Directions 2020, as directed by the then Secretary of State for Health. The Wave 2 follow-up was conducted in 2021, and Wave 3 in 2022.

Further information can be found on the NHS Digital Mental Health of Children and Young People Surveys webpage.

A similar series covering adults, the Adult Surveys of Psychiatric Morbidity, is also commissioned by NHS Digital.

The primary purpose of the Mental Health of Children and Adolescents in Great Britain, 1999 survey was to produce prevalence rates of three main categories of mental disorder:
conduct disorder;
hyperactivity;
emotional disorders (and their comorbidity);
based on ICD-10 (International Classification of Diseases, tenth revision) and DSM-IV (Diagnostic and Statistical Manual, fourth revision) criteria. Where there were sufficient numbers, the survey also aimed to provide prevalence rates of type of problem (e.g., separation anxiety, social phobia etc.) and to investigate the comorbidity or co-occurrence of disorders.

The Future of Families and Child Wellbeing Study (FFCWS, formerly known as the Fragile Families and Child Wellbeing Study) follows a cohort of nearly 5,000 children born in large, U.S. cities between 1998 and 2000. The study oversampled births to unmarried couples; and, when weighted, the data are representative of births in large U.S. cities at the turn of the century. The FFCWS was originally designed to address four questions of great interest to researchers and policy makers: What are the conditions and capabilities of unmarried parents, especially fathers? What is the nature of the relationships between unmarried parents? How do children born into these families fare? How do policies and environmental conditions affect families and children? The FFCWS consists of interviews with mothers, fathers, and/or primary caregivers at birth and again when children are ages 1, 3, 5, 9, 15, and 22. The parent interviews collected information on attitudes, relationships, parenting behavior, demographic characteristics, health (mental and physical), economic and employment status, neighborhood characteristics, and program participation. Beginning at age 9, children were interviewed directly (either during the home visit or on the telephone). The direct child interviews collected data on family relationships, home routines, schools, peers, and physical and mental health, as well as health behaviors. A collaborative study of the FFCWS, the In-Home Longitudinal Study of Pre-School Aged Children (In-Home Study) collected data from a subset of the FFCWS Core respondents at the Year 3 and 5 follow-ups to ask how parental resources in the form of parental presence or absence, time, and money influence children under the age of 5. The In-Home Study collected information on a variety of domains of the child's environment, including: the physical environment (quality of housing, nutrition and food security, health care, adequacy of clothing and supervision) and parenting (parental discipline, parental attachment, and cognitive stimulation). In addition, the In-Home Study also collected information on several important child outcomes, including anthropometrics, child behaviors, and cognitive ability. This information was collected through interviews with the child's primary caregiver, and direct observation of the child's home environment and the child's interactions with his or her caregiver. Similar activities were conducted during the Year 9 follow-up. At the Year 15 follow-up, a condensed set of home visit activities were conducted with a subsample of approximately 1,000 teens. Teens who participated in the In-Home Study were also invited to participate in a Sleep Study and were asked to wear an accelerometer on their non-dominant wrist for seven consecutive days to track their sleep (Sleep Actigraphy Data) and that day's behaviors and mood (Daily Sleep Actigraphy and Diary Survey Data). An additional collaborative study collected data from the child care provider (Year 3) and teacher (Years 9 and 15) through mail-based surveys. Saliva samples were collected at Year 9 and 15 (Biomarker file and Polygenic Scores). The Study of Adolescent Neural Development (SAND) COVID Study began data collection in May 2020 following the onset of the COVID-19 pandemic. It included online surveys with the young adult and their primary caregiver. The FFCWS began its seventh wave of data collection in October 2020, around the focal child's 22nd birthday. Data collection and interviews continued through January 2024. The Year 22 wave included a young adult (YA) survey with the original focal child and a primary caregiver (PCG) survey. Data were also collected on the children of the original focal child (referred to as Generation 3, or G3). Documentation for these files is available on the FFCWS website located here. For details of updates made to the FFCWS data files, please see the project's Data Alerts page. Data collection for the Future of Families and Child Wellbeing Study was supported by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) of the National Institutes of Health under award numbers R01HD36916, R01HD39135, and R01HD40421, as well as a consortium of private foundations.

aDemographic Characteristics of children and adolescent participants by ETD, National Health and Nutritional Examination Surveys, 2005–2010 (N = 2977).

Health Behavior in School-Aged Children (HBSC) started in 1984. Five countries participated in the first round. Since then, the project has grown to become a major cross-national survey with more than 40 member countries. The survey is conducted every fourth year among 11, 13 and 15 year old students. The purpose is to gather information about schoolchildren's health behaviors and well-being. Data is used for research as well as factual basis for policy making. The WHO Regional Office for Europe is an important partner in the project.

The HBSC Data Management Centre coordinates the work with the international datafile and the trend data, and is the Data Bank for the HBSC-study. The centre distributes data in accordance with the HBSC data access policy.

Introduction: Screentime is ubiquitous with children and parents concerned and anxious about its effect on the well-being of their children. This project uses the 2020 data from the National Survey of Children’s Health (NSCH) to determine if there is a correlation between the amount of weekday screentime in children ages 17 and younger and reported instances of mental health treatment and mental health treatment needed. Objectives: The primary objective of this project is to determine if there is a correlation between screentime and the mental health of children, ages 17 and younger. Methods: This project utilizes 2020 data from the NSCH, specifically the survey information collected about children ages 17 and younger on screentime, mental health professional treatment, and age of the child. Screentime refers to weekday time spent in front of a TV, computer, cellphone, or other electronic device watching programs, playing games, accessing the internet or using social media. After analyzing the three aforementioned variables, the percentage of mental health treatment occurrences by age group per screen time category indicates whether there is a correlation between children’s screentime and their mental health. Results: Preschool-aged (0-5 years old) children who spent 2 hours per weekday in front of a screen had the highest occurrence of mental health treatment, doubling the other categories of screentime. In school-aged (6-13 years old) children, there is a rise in mental health treatment needed as screentime increases. In adolescent (14-17 years old) children, there is a significant increase in the occurrence of mental health treatment as screentime increases, where 60% of adolescents who require mental health treatment spent four or more hours in front of a screen. Conclusions: There is a correlation between increased screentime and the occurrence of mental health treatment in children, particularly with the Adolescent (14-17 years old) age group.

The objective of the Young Minds Matter survey was to estimate the prevalence, severity, and impact of mental disorders in children and adolescents in Australia. Seven mental disorders were assessed using the parent or carer completed version of the Diagnostic Interview Schedule for Children Version IV (DISC-IV), and major depressive disorder was also assessed using the youth self-report version of the DISC-IV. Severity and impact were assessed using an extended version of the DISC-IV impact on functioning questions, and days absent from school due to symptoms of mental disorders. Data were collected in a national face-to-face survey of 6,310 parents or carers of children and adolescents aged 4-17 years, accompanied by self-report surveys of 2,969 young people aged 11-17 years. The 12-month prevalence of mental disorders was 13.9%. The most common class of disorders was ADHD followed by anxiety disorders. Mental disorders were more common in step-, blended- or one parent families, in families living in rented accommodation and families where one or both carers were not in employment. Some 2.1% of children and adolescents had severe disorders, 3.5% had moderate disorders and 8.3% had mild disorders. Mental disorders were associated with a substantial number of days absent from school, particularly in adolescents.

This mixed method, in-depth case study in Colorado examines the degree to which key players in the child welfare, early intervention/preschool special education (EI/Preschool SPED) and early care and education (ECE) systems (e.g. Head Start, preschool, child care centers, family child care homes) collaborate to meet the developmental needs of children ages 0-5 who are involved in the child welfare system. An ecological perspective serves as the conceptual framework to support the goals of the project and to guide the development of this study (Bronfenbrenner, 1979). This research includes a quantitative analysis of data from the National Survey of Child and Adolescent Wellbeing (NSCAW, a nationally representative sample of children involved in the child welfare system). Additional quantitative research was conducted through two surveys (optional paper or on-line survey) in Colorado between 2005-2006: the Foster Parent Survey, a statewide survey of foster parents drawn from public and private agency lists of licensed families (n=266), and the Child Welfare Caseworker Survey, a statewide survey of child welfare caseworkers and caseworker supervisors drawn from public and private agency lists (n=339). The qualitative component of this research was conducted through field study interviews, with professionals (Child Welfare, Early Intervention, and Early Care and Education) and foster and biological parents of children under 5 in the child welfare system. These interviews were conducted in Adams, Alamosa, Arapahoe, Conejos, and El Paso counties (n=134).