November 2017 A Report to Congress Highlights Child Well-Being Key Considerations for Policymakers Highlights of GAO-18-41SP Including the Need for a Federal Cross-Agency Priority Goal Enhancing the well-being of our The long-term success of a nation depends in large part on how well families children—one of the nation’s and society care for their children. Child well-being can be measured most valuable assets—requires through various indicators that reflect a child’s family, physical, and social a coordinated federal approach environments, health, and education. This report examines what is known that takes into account the about the state of child well-being and discusses selected experts’ views on interrelatedness of federal what policymakers could consider when addressing it. While many factors actions and policies that aim influence a child’s well-being, poverty—particularly early in life—can have to improve the lives of children. long-term consequences in many areas, such as the ability to be successful in school and work. In 2016, about 18 percent of children in the United States lived in poverty, with some groups faring worse than others. Estimated Percentage of U.S. Children Living in Poverty, by Race and Ethnicity For this report, GAO reviewed published federal data on select child well-being indicators, and interviewed federal officials and officials from 18 organizations that conduct research on children and family issues, selected to provide balance and coverage by subject matter expertise and to provide a range of viewpoints. Note: Estimates for Black children have a margin of error no greater than plus or minus 2.3 percentage points; for Hispanic children plus or minus 1.7; and for White children and all children no greater than plus or minus 0.8 percentage points. All estimates are at the 95 percent level of confidence. The federal poverty thresholds are updated by the U.S. Census Bureau each year; in 2016, the poverty threshold for a family of four with two children was $24,339. Section 1: Federal Data Show In recent years, the well-being of children in the United States has improved in That Child Well-Being Has some areas but not in others, and well-being continues to be generally worse Improved in Some Areas but for children who are minority, poor, and/or from families headed by single Not in Others, and Children mothers (compared to married parents), according to the federal data GAO with Certain Characteristics reviewed. Federal data show higher high school graduation rates and a greater Have Fared Worse than Others percentage of children who have health insurance, although this varied based on children’s characteristics. View GAO-18-41SP. For more information, contact Kathryn A. Larin at (202) 512-7215 or larink@gao.gov. Note: “Federal poverty level” refers to the U.S. Census Bureau’s poverty thresholds for the previous calendar year. Areas where children have fared worse over the last decade include depression and student homelessness. In school year 2014-15, about 1.26 million students were identified as homeless by public school districts, compared to less than one million in school year 2005-06. The percentage of households with food-insecure children—i.e. children who do not have access at all times to enough food for an active, healthy life—stayed about the same over the last decade, with female-headed households having the greatest percentage of food-insecure children. Note: Data are based on the U.S. Department of Agriculture’s measure of food security calculated from responses to a series of questions about the conditions and behaviors that characterize households when they are having difficulty meeting basic food needs. Section 2: Experts Noted Experts interviewed by GAO expressed a range of viewpoints on how Several Considerations policymakers could address child well-being, such as considering the whole for Policymakers Seeking family when addressing the needs of children and coordinating efforts among to Address the Multiple federal, state, local, and non-governmental entities, among other areas. Dimensions of Child Well-Being Experts suggested that policymakers consider ways to support a family’s ability to provide the safe, supportive, and nurturing environment that children need. For example, some experts highlighted the role of policies that promote marriage or encourage the maintenance of two-income households. With respect to coordination, experts discussed the importance of federal agencies coordinating with stakeholders inside and outside government to address child well-being. At the federal level, several experts suggested that efforts to address child well-being are hindered by insufficient coordination, noting that federal agencies generally lack the multidisciplinary structure needed for a coordinated approach. The Office of Management and Budget (OMB) is required to coordinate with agencies to develop federal government priority goals (known as cross-agency priority or CAP goals). These are long- term, outcome-oriented goals that cover a limited number of crosscutting policy areas. To date, child well-being has not been designated as a CAP goal. OMB is reviewing the current administration’s priorities to help develop new goals. By highlighting child well-being as an overarching priority area and ensuring that this priority is reflected in agencies’ strategic plans, OMB could help draw needed attention to federal efforts to improve child well-being. Recommendation GAO recommends that OMB consider developing a goal that addresses a for Executive Action coordinated federal approach to child well-being among its next set of cross-agency priority, or CAP, goals, including working with relevant agencies to ensure their strategic plans include related goals and objectives. OMB neither agreed nor disagreed with the recommendation and noted that it is currently in the process of developing the next set of CAP goals. Contents Preface 1 Section 1: Federal Data Show That Child Well-Being Has Improved in Some Areas but Not in Others, and Children with Certain Characteristics Have Fared Worse than Others 9 Section 2: Experts Noted Several Considerations for Policymakers Seeking to Address the Multiple Dimensions of Child Well-Being 35 Conclusions 44 Recommendation for Executive Action 44 Agency Comments 44 Appendix I Scope and Methodology 46 Appendix II Selected Child Well-Being Frameworks 49 Appendix III List of Expert Organizations 51 Appendix IV Related GAO Products 52 Appendix V GAO Contact and Staff Acknowledgments 60 Figures Figure 1: Estimated Percentage of U.S. Children Living in Poverty, by Race and Ethnicity, 2007-2016 3 Figure 2: Selected Indicators of Child Well-Being 7 Figure 3: Family, Physical, and Social Environment Indicators of Child Well-Being 10 Figure 4: Food Insecurity 11 Figure 5: Student and Family Homelessness 12 Figure 6: Child Maltreatment 13 Page i GAO-18-41SP Child Well-Being Figure 7: Neighborhood Safety 14 Figure 8: Neighborhood Housing Quality 15 Figure 9: Death Due to Accidental Injury 16 Figure 10: Homicide 17 Figure 11: Physical and Mental Health Indicators of Child Well- Being 19 Figure 12: Birth Outcomes 20 Figure 13: Access to Insurance and Medical Care 21 Figure 14: Obesity 22 Figure 15: Asthma 23 Figure 16: Depression and Suicide 24 Figure 17: Alcohol, Smoking, and Drug Use 25 Figure 18: Early Care and Education Indicators of Child Well- Being 27 Figure 19: Cost and Quality of Child Care 28 Figure 20: Preschool Enrollment 29 Figure 21: Access to College-prep Courses and High School Graduation Rates 30 Figure 22: Reading Scores 31 Figure 23: Math Scores 32 Figure 24: Student Suspensions 33 Figure 25: School Crime and Safety 34 Abbreviations CAP goals Cross-agency priority goals CDC Centers for Disease Control and Prevention ERS Economic Research Service HHS U.S. Department of Health and Human Services HUD U.S. Department of Housing and Urban Development K-12 Kindergarten through 12th grade OMB Office of Management and Budget Page ii GAO-18-41SP Child Well-Being Source of cover images (clockwise from top left): Digital Vision, U.S. Department of Health and Human Services’ Centers for Disease Control and Prevention Public Health Image Library, Digital Vision, Digital Vision, U.S. Department of Health and Human Services’ Centers for Disease Control and Prevention Public Health Image Library. This is a work of the U.S. government and is not subject to copyright protection in the United States. The published product may be reproduced and distributed in its entirety without further permission from GAO. However, because this work may contain copyrighted images or other material, permission from the copyright holder may be necessary if you wish to reproduce this material separately. Page iii GAO-18-41SP Child Well-Being Letter 441 G St. N.W. Washington, DC 20548 Preface November 9, 2017 The well-being of the nation’s children is critical to our country’s prosperity, and understanding how children are faring across various areas is important to addressing their needs. The success of the nation depends in large part on how well families, and society as a whole, can ensure that its nearly 74 million children grow up in safe and healthy environments and become responsible and productive adults. Research suggests that adverse experiences in childhood can lead to negative outcomes throughout one’s life—including poor health and academic performance, as well as unemployment, all of which not only adversely affect the individual, but also the strength of the nation’s social and economic sectors. 1 While there is not a single definition of child well- being, it is widely considered to be influenced by a variety of factors, including the extent to which children’s basic and other needs are met within the context of their families, communities, and society at large. Accordingly, child well-being can be measured across a range of indicators that reflect the family, physical, and social environments in which children live, as well as their health and educational experiences. While many factors influence a child’s well-being, living in poverty— especially early in life—can have wide-ranging ramifications in a host of 1 See the U.S. Department of Health and Human Services’ Centers for Disease Control and Prevention-Kaiser Permanente’s Adverse Childhood Experiences Study. This study— one of the largest investigations of childhood abuse and neglect and later-life health and well-being—found that the risk of negative health and well-being outcomes across one’s life course (e.g., depression, unintended pregnancy, poor academic achievement, and poor work performance) increased as the number of challenges faced as children increased. The challenges in the study included abuse, neglect, and household challenges, such as divorce or parental mental illness. Page 1 GAO-18-41SP Child Well-Being areas. 2 Children who experience poverty are often more likely to face academic and social challenges, live in adverse conditions, and have poorer health than children who grow up in higher-income families. These adverse outcomes tend to limit the development of skills and abilities needed to contribute productively to the economy. From 2007 to 2016, the estimated percentage of all children living in poverty in the United States remained about the same at 18 percent, after peaking in 2010 at 22 percent, according to U.S. Census Bureau (Census) data. 3 Some groups of children fared worse than others. Black and Hispanic children, for example, experienced poverty at significantly higher rates than White children during this time period (see fig. 1). 2 The official poverty thresholds—the income thresholds by which households are considered to be in poverty depending on their size and composition—are updated annually by the U.S. Census Bureau (Census) to reflect current prices. The U.S. Department of Health and Human Services (HHS) uses the official poverty thresholds to update the “federal poverty guidelines” each year, which are the basis for determining eligibility or funding distribution for certain federal programs. The federal poverty guidelines issued by HHS are a simplified version of the official poverty thresholds issued by Census and there are some differences between two measures. For instance, the HHS guidelines vary by family size, while the Census poverty thresholds vary by family size, number of children, and, for households with one or two people, whether these members are elderly. In addition, due to differences in the timing of when each measure is updated, the poverty guidelines are approximately equivalent to the poverty thresholds for the prior year. In determining a household’s income, the official measure considers cash income, but does not include additions to income based on the value of noncash assistance (e.g., food assistance) or reductions based on other necessary living expenses (e.g., medical expenses or taxes paid). In this report, references to the “federal poverty level” or “FPL” refer to Census’s federal poverty thresholds. 3 According to the U.S. Census Bureau’s Current Population Survey, while the poverty rate for children under 18 remained about the same from 2007 to 2016, it decreased between 2014 and 2016 from an estimated 21.1 percent to 18.0 percent. The poverty estimates for 2007, 2010, 2014, and 2016 have a margin of error no larger than plus or minus 0.72 percentage points at the 95 percent level of confidence. Page 2 GAO-18-41SP Child Well-Being Figure 1: Estimated Percentage of U.S. Children Living in Poverty, by Race and Ethnicity, 2007-2016 Notes: The data include all children less than 18 years of age. Black=Black alone and White=White alone. Estimates for Black children have a margin of error no greater than plus or minus 2.3 percentage points at the 95 percent level of confidence. Estimates for Hispanic children have a margin of error no greater than plus or minus 1.7 percentage points at the 95 percent level of confidence. Estimates for White children and all children have a margin of error no greater than plus or minus 0.8 percentage points at the 95 percent level of confidence. The federal poverty thresholds are updated by the U.S. Census Bureau each year; in 2016, the poverty threshold for a family of four people with two children was $24,339. Family composition also relates to poverty. For example, while an estimated 10 percent of families in the United States lived in poverty in 2016, single-parent families fared worse, according to Census data from the Current Population Survey. 4 Specifically, an estimated 27 percent of female-headed households and 13 percent of male-headed households 4 This refers to primary families. According to the U.S. Census Bureau, a primary family is a group of two or more people, one of whom is the householder, related by birth, marriage, or adoption and residing together. All such people (including related subfamily members) are considered as members of one family. Page 3 GAO-18-41SP Child Well-Being lived in poverty in 2016, compared to 5 percent of households with married couples. 5 According to studies by the U.S. Department of Agriculture’s Economic Research Service (ERS), children living in rural areas have higher poverty rates than children living in urban areas. ERS notes that the rise in rural child poverty is partly due to the fact that average incomes for rural families with children did not rise during the economic expansion of 2003- 07, and fell during the 2007-09 recession and the early years of the recovery. In 2015, rural (nonmetropolitan) child poverty declined to about 24 percent and urban child poverty declined to about 20 percent. 6 While families play an essential role in nurturing and providing for their children, the government also has a clear interest in promoting child well- being and does so in a variety of ways. States and localities help fund and administer programs to foster the well-being of children and families. The federal government also supports states by helping to fund many of these efforts. These include, for example, programs that provide medical, housing, food, and other types of assistance to eligible children and families, as well as those that promote equitable educational opportunities and tax policies. These programs can play a key role in enhancing the well-being of low-income families and children. While official poverty statistics incorporate cash assistance received by families, they do not reflect non-cash assistance provided by these government programs. The U.S. Census Bureau developed the Supplemental Poverty Measure as an alternative measure to take into account non-cash assistance provided by 5 These estimates of poverty by type of family have a margin of error no greater than plus or minus 1.3 percentage points at the 95 percent level of confidence. See Jessica L. Semega, Kayla R. Fontenot, and Melissa A. Kollar, U.S. Census Bureau, Current Population Reports, P60-259, Income and Poverty in the United States: 2016, U.S. Government Printing Office, Washington, D.C., 2017. 6 The specific rural child poverty data cited are derived from the American Community Survey, which, according to ERS, the U.S. Census Bureau recommends using because it has a much larger sample size than the Current Population Survey. However, as ERS states in its study on rural poverty, the American Community Survey does not allow for the same historical perspective as does the Current Population Survey, and the two surveys are not directly comparable, given that the design of the American Community Survey differs from that of the Current Population Survey in a variety of ways and may produce somewhat different poverty estimates. ERS did not provide a statement of sampling error associated with these estimates. See U.S. Department of Agriculture, Economic Research Service, “Poverty Overview” updated March 2017; https://www.ers.usda.gov/topics/rural- economy-population/rural-poverty-well-being/poverty-overview.aspx; and Understanding the Rise in Rural Child Poverty, 2003-2014, USDA, Economic Research Service, May 2016. Page 4 GAO-18-41SP Child Well-Being many government programs designed to assist low-income families. The Supplemental Poverty Measure rate for children was lower in 2016 than the poverty rate under the official poverty measure. 7 In addition to administering programs that support low-income families, federal agencies also conduct and sponsor evaluations of programs and some have established goals designed to improve the state of child well- being. Federal agencies also collect and disseminate data that can be used to help gauge progress toward these goals and may also work together to address and draw attention to society-wide issues related to child well-being. For example, the United States Interagency Council on Homelessness, which includes 19 federal agencies, established goals to work together to end youth and family homelessness. A similar effort— Healthy People—provides a comprehensive set of 10-year national goals and objectives for improving the health of all Americans, including specific indicators pertaining to children. 8 Many entities, including non-profit organizations and federal government agencies, recognize the importance of child well-being and have developed frameworks to measure how well children in the United States are faring. For example, the Federal Interagency Forum on Child and Family Statistics (the Forum) publishes an annual report that includes a summary of national indicators of child well-being. 9 The Forum is a 7 The U.S. Census Bureau developed the Supplemental Poverty Measure in 2010 with support from the U.S. Department of Labor’s Bureau of Labor Statistics. This measure includes all the same components under cash income as the official measure, but adds non-cash benefits, such as housing and food assistance, and subtracts expenses, such as child care and medical expenses, to reach a final measure of household resources. According to a recent U.S. Census Bureau report, the poverty rate for children in 2016 was 15.2 percent when measured using the Supplemental Poverty Measure, compared to 18 percent using the official poverty measure. The 95 percent confidence interval for these estimates are (14.6, 15.8) and (17.4, 18.6), respectively. See U.S. Department of Commerce Economics and Statistics Administration, U.S. Census Bureau, The Supplemental Poverty Measure: 2016, Current Population Reports, Revised September 2017. 8 A federal interagency workgroup led the Healthy People 2020 development effort. The workgroup drew on the diverse backgrounds of its member agencies, lessons learned from past Healthy People efforts, broad-based public comment, and the work of the Secretary of Health and Human Services’ Advisory Committee on National Health Promotion and Disease Prevention Objectives for 2020. 9 Federal Interagency Forum on Child and Family Statistics. America’s Children in Brief: Key National Indicators of Well-Being, 2016. Washington, D.C.: U.S. Government Printing Office. The Forum was established by section 6 of Executive Order 13045, 62 Fed. Reg.19,885, 19,887 (Apr. 23, 1997). Page 5 GAO-18-41SP Child Well-Being collaboration of 23 federal agencies, and its mission is to foster coordination and collaboration and to enhance and improve consistency in the collection and reporting of federal data on children and families. The Forum also aims to improve the reporting and dissemination of information on the status of children and families. It does not, however, focus on programs or policies related to child well-being or coordinate efforts to improve or implement these programs among federal agencies, according to Forum officials. There are many other organizations and researchers—both domestically and internationally—that have also developed frameworks and published child well-being indicators (see app. II for a selected list of these organizations and associated frameworks). This report (1) examines what is known about the state of child well-being in the United States and how it has changed in recent years, and (2) discusses selected experts’ views on what policymakers could consider in addressing child well-being. We reviewed select federal data related to several indicators of child well-being and, after reviewing several child well-being frameworks and discussing these indicators with a variety of subject matter experts, we selected and categorized indicators along three main areas of a child’s life: (1) family, physical, and social environment; (2) physical and mental health; and (3) early care and education (see fig. 2). Page 6 GAO-18-41SP Child Well-Being Figure 2: Selected Indicators of Child Well-Being For each child well-being indicator, we reviewed published federal data for children overall over the most recent 10-year period, and by certain characteristics—race/ethnicity, income level/poverty status, and family composition—for the first and last years of the 10-year period, to the extent data were available. We assessed the reliability of the data by (1) reviewing existing information about the data and the system that produced them, and, in some cases, (2) interviewing agency officials knowledgeable about the data. We determined that the data were sufficiently reliable for the purposes of this report. We interviewed federal agency officials from the U.S. Office of Management and Budget (OMB), Department of Agriculture’s ERS, Department of Education’s National Center for Education Statistics, Department of Health and Human Services’ (HHS) Centers for Disease Control and Prevention (CDC), and Page 7 GAO-18-41SP Child Well-Being HHS’s Assistant Secretary for Planning and Evaluation about child well- being issues and related data. We also interviewed officials with subject matter expertise in child well-being from 18 non-governmental organizations that were selected to provide variation across areas of expertise and a wide range of viewpoints, including perspectives on the role of the federal government. The information and perspectives we obtained and present in this report should not be regarded as an exhaustive discussion that includes all viewpoints of experts on child well- being issues, nor is it generalizable to all child well-being experts. The viewpoints summarized in this report also do not necessarily represent the views of all the experts we interviewed, their organizations, or GAO. See appendix I for a complete discussion of our methodology. We conducted this performance audit from March 2016 to November 2017 in accordance with generally accepted government auditing standards. Those standards require that we plan and perform the audit to obtain sufficient, appropriate evidence to provide a reasonable basis for our findings and conclusions based on our audit objectives. We believe that the evidence obtained provides a reasonable basis for our findings and conclusions based on our audit objectives. Readers who are interested in more in-depth discussions of child well- being issues may refer to the list of related GAO products at the end of this report (appendix IV). This report was prepared under the direction of Kathryn A. Larin, Director, Education, Workforce, and Income Security Issues, who may be reached at (202) 512-7215 or larink@gao.gov. GAO staff who made key contributions to this publication are listed in appendix V. Contact points for our Offices of Congressional Relations and Public Affairs may be found on the last page of this publication. In addition, this publication will be available at no charge on GAO’s website at http://www.gao.gov. Gene L. Dodaro Comptroller General of the United States Page 8 GAO-18-41SP Child Well-Being Section 1: Federal Data Show That Child Well- Section 1: Federal Data Show That Child Well- Being Has Improved in Some Areas but Not in Others, and Children with Certain Being Has Improved in Some Areas but Not in Characteristics Have Fared Worse than Others Others, and Children with Certain Characteristics Have Fared Worse than Others In recent years, the well-being of children in the United States has improved in some areas but not in others, according to the federal data we reviewed, and well-being continues to be generally worse for children who are minority, poor, and/or from families headed by single mothers (compared to married parents). For example, while data show greater health insurance coverage and higher high school graduation rates in recent years, children and youth fared worse in areas such as homelessness and major depression. Data also show that the disparities (also referred to as gaps) in well-being that exist among children across different racial/ethnic groups, income levels, and families of varying compositions have persisted, though, in some cases, these have narrowed over time. For example, the homicide rate of Black 15 to 19 year olds in 2014 was significantly higher than that of Whites in the same age group, though the gap in their homicide rates narrowed over the last decade. In another example, Black, Hispanic, and poor students’ estimated average reading and math scores were worse than their White and non-poor peers, though the achievement gaps between Black and White students and between Hispanic and White students narrowed a few points for 4th and 8th grade, but stayed about the same for 12th grade. The gaps between poor students and their non-poor peers remained about the same across reading and math scores. Family, Physical, and Over the last decade, federal data we reviewed show that changes in the Social Environment of family, physical, and social environments of children overall have been mixed, and, in general, children with certain characteristics have fared Children worse than others (see fig. 3 below for the indicators we reviewed). For example, the estimated percentage of households with food-insecure children was about the same in 2016 as in 2007; however, in 2016, the estimated percentage of Black and Hispanic households with food- insecure children was higher than that of White households, and single- mother households had higher estimated rates of food insecure-children than married-couple households in that same year. 1 In other areas, the family, physical, and social environment of children improved over time for children in certain age groups. From 2005 to 2014, death rates due to accidental injuries, such as drowning, decreased for all teenagers age 15 1 According to the U.S. Department of Agriculture, households with food-insecure children are those households in which children do not have access at all times to enough food for an active, healthy life. Page 9 GAO-18-41SP Child Well-Being Section 1: Federal Data Show That Child Well- Being Has Improved in Some Areas but Not in Others, and Children with Certain Characteristics Have Fared Worse than Others to 19. 2 However, the accidental death rate of American Indian/Alaska Native youth age 15 to 19 in 2014 was higher than that of their White peers. One area where children overall fared worse was homelessness; a greater number of enrolled public school students were homeless in school year 2014-15 than in 2005-06. (See figs. 4–10.) Figure 3: Family, Physical, and Social Environment Indicators of Child Well-Being 2 Death rates due to accidental injuries also decreased for children ages 1-4, 5-9, and 10- 14, but increased for infants under 1 year over the same period. Page 10 GAO-18-41SP Child Well-Being Section 1: Federal Data Show That Child Well- Being Has Improved in Some Areas but Not in Others, and Children with Certain Characteristics Have Fared Worse than Others Figure 4: Food Insecurity Notes: The household food security statistics are based on a measure of food security calculated from responses to a series of questions about conditions and behaviors that characterize households when they are having difficulty meeting basic food needs. Households are classified as having food-insecure children if they report two or more food-insecure conditions among the children in response to certain questions. For race and ethnicity data, “White”=White, non-Hispanic; “Black”=Black, non-Hispanic; and “Other”=Other, non-Hispanic. Hispanics may be of any race. For income level data, a household’s poverty status was determined based on family income, size, and composition, using the U.S. Census Bureau’s poverty thresholds (referred to in the figure as the “federal poverty level”). For more information, see Alisha Coleman-Jensen, Matthew P. Rabbitt, Christian A. Gregory, and Anita Singh, Household Food Security in the United States in 2016, ERR-237 (U.S. Department of Agriculture, Economic Research Service, September 2017). a See Alisha Coleman-Jensen, Matthew P. Rabbitt, Christian A. Gregory, and Anita Singh, Household Food Security in the United States in 2016, ERR-237 (U.S. Department of Agriculture, Economic Research Service, September 2017). Page 11 GAO-18-41SP Child Well-Being Section 1: Federal Data Show That Child Well- Being Has Improved in Some Areas but Not in Others, and Children with Certain Characteristics Have Fared Worse than Others Figure 5: Student and Family Homelessness Notes: According to the National Center for Homeless Education (NCHE), homeless students reported as enrolled in public school districts by state educational agencies represent an unduplicated count of students from the 50 states, the District of Columbia, and Puerto Rico. See NCHE, Federal Data Summary: School Years 2012-13 to 2014-15, Education for Homeless Children and Youth (Browns Summit, NC, 2016). According to the U.S. Department of Housing and Urban Development (HUD), the one-year estimates account for all people who used an emergency shelter or transitional housing program as part of a family with children at any time from October 1 through September 30 of the reporting year. HUD data do not include people who are “doubled-up.” See HUD, Office of Community Planning and Development, The 2015 Annual Homeless Assessment Report (AHAR) to Congress Part 2: Estimates of Homelessness in the United States (October 2016). a See U.S. Department of Health and Human Services, Well-being of Young Children after Experiencing Homelessness, Homeless Families Research Brief OPRE Report No. 2017-06 (January 2017). Page 12 GAO-18-41SP Child Well-Being Section 1: Federal Data Show That Child Well- Being Has Improved in Some Areas but Not in Others, and Children with Certain Characteristics Have Fared Worse than Others Figure 6: Child Maltreatment Notes: All states have child abuse and neglect reporting laws that mandate certain professionals and institutions refer suspected maltreatment to a child protective services agency. Each state has its own definitions of child abuse and neglect, consistent with federal law. The Child Abuse Prevention and Treatment Act (CAPTA), as amended, defines child abuse and neglect as, at a minimum: any recent act or failure to act on the part of a parent or caretaker, which results in death, serious physical or emotional harm, sexual abuse or exploitation, or an act or failure to act which presents an imminent risk of serious harm. Data are submitted voluntarily to the U.S. Department of Health and Human Services by the 50 states, the District of Columbia, and the Commonwealth of Puerto Rico, and collected in the National Child Abuse and Neglect Data System (NCANDS). In NCANDS, a victim is defined as a child for whom the state determined that at least one instance of maltreatment was substantiated or indicated. The number of victims is a unique count. For race and ethnicity data, counts associated with each racial group are exclusive and do not include Hispanic ethnicity. AI/AN=American Indian or Alaska Native. For more information, see U.S. Department of Health & Human Services, Administration for Children and Families, Administration on Children, Youth and Families, Children’s Bureau, Child Maltreatment 2015 (2017). a See Federal Interagency Forum on Child and Family Statistics, America’s Children in Brief: Key National Indicators of Well-Being, 2016. (Washington, D.C.: U.S. Government Printing Office). . Page 13 GAO-18-41SP Child Well-Being Section 1: Federal Data Show That Child Well- Being Has Improved in Some Areas but Not in Others, and Children with Certain Characteristics Have Fared Worse than Others Figure 7: Neighborhood Safety Notes: The 2016 National Survey of Children’s Health (NSCH) asked the question, “Does this child live in a safe neighborhood?” Due to changes in the 2016 NSCH, including in the survey’s mode of data collection, sampling frame, and question wording, data from the 2016 survey cannot be compared to estimates from previous iterations of the survey. For race and ethnicity data, “White”=White, non- Hispanic; “Black”=Black, non-Hispanic; and “Other”=Other, non-Hispanic. For family income level data, information on total family income during the previous calendar year and the number of adult and child family members living in the child’s household was used to create an index of income relative to the U.S. Census Bureau’s poverty thresholds (referred to in the figure as the “federal poverty level”). For family composition data, “Married couple”=two parents, currently married; “Unmarried couple”=two-parents, not currently married; “Single-mother”=single mother (currently married but living apart, formerly married, or never married); and “Other”=other family type, no parent reported. For more information, see the Child and Adolescent Health Measurement Initiative, Data Resource Center for Child & Adolescent Health. a See Healthy People 2020 Social Determinants of Health framework. Page 14 GAO-18-41SP Child Well-Being Section 1: Federal Data Show That Child Well- Being Has Improved in Some Areas but Not in Others, and Children with Certain Characteristics Have Fared Worse than Others Figure 8: Neighborhood Housing Quality Notes: The 2016 National Survey of Children’s Health (NSCH) asked the question, “In your neighborhood, is there poorly kept or rundown housing?” Due to changes in the 2016 NSCH, including in the survey’s mode of data collection, sampling frame, and question wording, data from the 2016 survey cannot be compared to estimates from previous iterations of the survey. For race and ethnicity data, “White”=White, non-Hispanic; “Black”=Black, non-Hispanic; and “Other”=Other, non-Hispanic. For family income level data, information on total family income during the previous calendar year and the number of adult and child family members living in the child’s household was used to create an index of income relative to the U.S. Census Bureau’s poverty thresholds (referred to in the figure as the “federal poverty level”). For family composition data, “Married couple”=two parents, currently married; “Unmarried couple”=two-parents, not currently married; “Single-mother”=single mother (currently married but living apart, formerly married, or never married); and “Other”=other family type, no parent reported. For more information, see the Child and Adolescent Health Measurement Initiative, Data Resource Center for Child & Adolescent Health. a See U.S. Department of Housing and Urban Development, Office of Policy Development and Research, Housing’s and Neighborhood’s Role in Shaping Children’s Future, Evidence Matters (Fall 2014). Page 15 GAO-18-41SP Child Well-Being Section 1: Federal Data Show That Child Well- Being Has Improved in Some Areas but Not in Others, and Children with Certain Characteristics Have Fared Worse than Others Figure 9: Death Due to Accidental Injury Notes: Data are based on information from all death certificates filed in the 50 states and the District of Columbia in 2014, processed by the U.S. Department of Health and Human Services’ (HHS) National Center for Health Statistics. The accidental death rate for infants is the number of infant deaths due to unintentional injuries per 100,000 live births in specified group. For other age groups, it is the number of deaths due to unintentional injuries per 100,000 population in specified group. Asian=Asian or Pacific Islander. Deaths for races other than White or Black should be interpreted with caution. Race and Hispanic origin are reported separately on the death certificate. Data for Hispanic origin should be interpreted with caution because of inconsistencies between reporting Hispanic origin on birth and death certificates (for infants) and misreporting of Hispanic origin on the death certificate (for other age groups). The term “no data” in the figure refers to data that do not meet the agency’s standards of reliability or precision. See HHS, Centers for Disease Control and Prevention, Deaths: Leading Causes for 2014, National Vital Statistics Reports, Vol. 65, Number 5 (June 2016, amended June 2017). a Specifically, unintentional injuries were the leading cause of death for each of the following age groups: 1-4 years, 5-9 years, 10-14 years, and 15-19 years. See HHS, Centers for Disease Control and Prevention, Deaths: Leading Causes for 2014, National Vital Statistics Reports, Vol. 65, Number 5 (June 2016, amended June 2017). Page 16 GAO-18-41SP Child Well-Being Section 1: Federal Data Show That Child Well- Being Has Improved in Some Areas but Not in Others, and Children with Certain Characteristics Have Fared Worse than Others Figure 10: Homicide Notes: Data are based on information from all death certificates that were filed in the 50 states and the District of Columbia in 2014 and processed by the U.S. Department of Health and Human Services’ (HHS) National Center for Health Statistics. Data are reported here for post-neonates rather than for all infants (under 1 year) as homicide was not among the top 10 leading causes of death for infants (all races, both sexes) from 2005 to 2014.The homicide rate for post-neonates is the number of deaths due to assault per 100,000 live births in specified group. For other age groups, it is the number of deaths due to assault per 100,000 population in specified group. “White”=Non-Hispanic White; “Black”=Non-Hispanic Black. Data for Hispanic origin include persons of any race. Deaths are based on race of decedent; live births are based on race of mother. Race and Hispanic origin are reported separately on the death certificate. Due to inconsistencies with reporting, data for Hispanic origin should be interpreted with caution. See HHS, Centers for Disease Control and Prevention, Deaths: Leading Causes for 2014, National Vital Statistics Reports, Vol. 65, Number 5 (June 2016, amended June 2017). a Specifically, homicide ranked among the top five leading causes of death for each of the following age groups: post-neonates, 1-4 years, 5-9 years, 10-14 years, and 15-19 years. See HHS, Centers for Disease Control and Prevention, Deaths: Leading Causes for 2014, National Vital Statistics Reports, Vol. 65, Number 5 (June 2016, amended June 2017). Page 17 GAO-18-41SP Child Well-Being Section 1: Federal Data Show That Child Well- Being Has Improved in Some Areas but Not in Others, and Children with Certain Characteristics Have Fared Worse than Others Physical and Mental According to the last 10 years of federal data we reviewed, children’s Health of Children physical and mental health has improved in some areas, worsened in others, or had no change overall across different health indicators, and children with certain characteristics fared worse than others (see fig. 11 below for the indicators we reviewed). Estimated health insurance coverage and access to medical and dental care (as measured by unmet medical and dental needs due to cost) improved for children of all income levels from 2006 to 2015, though access to care was significantly worse for the poorest children than for those from the highest income category in 2015. On the other hand, from 2005 to 2014, the suicide rate of youth age 15 to 19 rose slightly, and in both 2005 and 2014, non-Hispanic White youth had higher suicide rates than both non-Hispanic Black and Hispanic youth. These disparities increased due to higher reported rates for White youth. 3 Data on asthma show that the estimated percentage of children with asthma stayed about the same over the last several years, but a higher percentage of children with asthma in 2015 were Black versus White or Hispanic; in poverty versus from the highest income group; and/or lived with a single mother versus two parents. Similarly, 2016 data on obesity show that children age 10 to 17 who were Black, Hispanic, or poor had the highest reported rates of obesity. (See figs. 12- 17.) 3 However, death certificate data from the Centers for Disease Control and Prevention’s National Vital Statistics System are limited by changes to the classification of death from 2005 to 2014 and the potential misclassification of suicide as the underlying cause of death. In 2005, the suicide rates among children age 15-19 per 100,000 youth in the population were: Non-Hispanic White (8.8); Non-Hispanic Black (4.5); and Hispanic (6.1). In 2014, the rates were: Non-Hispanic White (10.9); Non-Hispanic Black (4.5); and Hispanic (6.0). Page 18 GAO-18-41SP Child Well-Being Section 1: Federal Data Show That Child Well- Being Has Improved in Some Areas but Not in Others, and Children with Certain Characteristics Have Fared Worse than Others Figure 11: Physical and Mental Health Indicators of Child Well-Being Page 19 GAO-18-41SP Child Well-Being Section 1: Federal Data Show That Child Well- Being Has Improved in Some Areas but Not in Others, and Children with Certain Characteristics Have Fared Worse than Others Figure 12: Birth Outcomes Notes: Data shown in this figure for 2015 and 2016 are based on information derived from birth certificates and includes information for all births occurring in the United States. The data are provided to the U.S. Department of Health and Human Services’ National Center for Health Statistics through the Vital Statistics Cooperative Program. Preterm births are births of less than 37 completed weeks of gestation based on the obstetric estimate of gestation. Low birthweight is less than 2,500 grams. For race and ethnicity data, “White”=Non-Hispanic White; and “Black”=Non-Hispanic Black. Race and Hispanic origin are reported separately on birth certificates. Persons of Hispanic origin may be of any race. For more information, see U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, Births in the United States, 2016, National Center for Health Statistics Data Brief No. 287 (September 2017) and Births: Final Data for 2015, National Vital Statistics Reports, Vol. 66, Number 1 (January 2017). See also Patrick, S.W., et al. (2015). Increasing Incidence and Geographic Distribution of Neonatal Abstinence Syndrome: United States 2009 to 2012. J Perinatol 35(8), pp. 650-655. a See Federal Interagency Forum on Child and Family Statistics, America’s Children: Key National Indicators of Well-Being, 2015 (Washington, D.C.: U.S. Government Printing Office). Page 20 GAO-18-41SP Child Well-Being Section 1: Federal Data Show That Child Well- Being Has Improved in Some Areas but Not in Others, and Children with Certain Characteristics Have Fared Worse than Others Figure 13: Access to Insurance and Medical Care Notes: Data are based on household interviews of a sample of the population. “White”=White, single race (not Hispanic or Latino); “Black”=Black or African American only, single race (not Hispanic or Latino). Children who are of Hispanic or Latino origin may be of any race(s). “Two parents”=Mother and Father. A household’s poverty status was determined using the U.S. Census Bureau’s poverty thresholds for the previous calendar year (referred to in the figure as the “federal poverty level”). Near poor persons have incomes of 100 percent to less than 200 percent of the federal poverty threshold. See U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Health Statistics, Summary Health Statistics: National Health Interview Survey. a See Federal Interagency Forum on Child and Family Statistics, America’s Children in Brief: Key National Indicators of Well-Being, 2016 (Washington, D.C.: U.S. Government Printing Office) and U.S. Department of Health and Human Services, Implementation of Project LAUNCH: Cross-site Evaluation Findings, Volume 1, OPRE Report 2014-87, 2014 (Washington, D.C.). Page 21 GAO-18-41SP Child Well-Being Section 1: Federal Data Show That Child Well- Being Has Improved in Some Areas but Not in Others, and Children with Certain Characteristics Have Fared Worse than Others Figure 14: Obesity Notes: The 2016 National Survey of Children’s Health (NSCH) asked the question, “What is the weight status of children (age 10-17 years) based on Body Mass Index (BMI) for age?” Underweight=less than 5th percentile; Healthy weight=5th to 84th percentile; Overweight=85th to 94th percentile; and Obese=95th percentile or above. Due to changes in the 2016 NSCH, including in the survey’s mode of data collection, sampling frame, and question wording, data from the 2016 survey cannot be compared to estimates from previous iterations of the survey. For race and ethnicity data, “White”=White, non- Hispanic; “Black”=Black, non-Hispanic; and “Other”=Other, non-Hispanic. For family income level data, information on total family income during the previous calendar year and the number of adult and child family members living in the child’s household was used to create an index of income relative to the U.S. Census Bureau’s poverty thresholds (referred to in the figure as the “fed. poverty level”). For family composition data, “Married couple”=two parents, currently married; “Unmarried couple”=two-parents, not currently married; “Single-mother”=single mother (currently married but living apart, formerly married, or never married); and “Other”=other family type, no parent reported. For more information, see the Child and Adolescent Health Measurement Initiative, Data Resource Center for Child & Adolescent Health. The Centers for Disease Control and Prevention reported that the prevalence of obesity in 2011-2014 among preschool-aged children (2-5 years) was 8.9 percent; school-aged children (6-11 years) was 17.5 percent; and adolescents (12-19 years) was 20.5 percent. a See Federal Interagency Forum on Child and Family Statistics, America’s Children in Brief: Key National Indicators of Well-Being, 2016. (Washington, D.C.: U.S. Government Printing Office). Page 22 GAO-18-41SP Child Well-Being Section 1: Federal Data Show That Child Well- Being Has Improved in Some Areas but Not in Others, and Children with Certain Characteristics Have Fared Worse than Others Figure 15: Asthma Notes: Data are based on household interviews of a sample of the civilian noninstitutionalized population. The data are based on responses about the sample child, not all children in the family. For race and ethnicity data, “White”=White, single race, non-Hispanic; “Black”=Black, single race, non-Hispanic. Persons of Hispanic or Latino origin may be of any race or combination of races. For income level data, a household’s poverty status was determined based on family income in the previous calendar year, size, and composition, using the U.S. Census Bureau’s poverty thresholds for the previous calendar year (referred to in the figure as the “federal poverty level”). Family composition data refer to parents living in the household. “Two parents”=Mother and Father. Mother and father can include biological, adoptive, step, in-law, or foster relationships. “Single-mother”=Mother, no father; “Single-father”=Father, no mother; and “Other”=Neither mother nor father. Legal guardians are classified in neither mother nor father. For more information, see U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Health Statistics, Summary Health Statistics: National Health Interview Survey. a See Federal Interagency Forum on Child and Family Statistics, America’s Children in Brief: Key National Indicators of Well-Being, 2016. (Washington, D.C.: U.S. Government Printing Office) and Centers for Disease Control and Prevention, Asthma’s Impact on the Nation: Data from the CDC National Asthma Control Program. Page 23 GAO-18-41SP Child Well-Being Section 1: Federal Data Show That Child Well- Being Has Improved in Some Areas but Not in Others, and Children with Certain Characteristics Have Fared Worse than Others Figure 16: Depression and Suicide Notes: Major Depressive Episode (MDE) specifies a period of at least 2 weeks when a person experienced a depressed mood or loss of interest or pleasure in daily activities and had a majority of specified depression symptoms. The data refer to youth who had at least one MDE in the past year. Treatment is defined as seeing or talking to a health or alternative service professional or using prescription medication for depression in the past year. The data refer to youth who received treatment for depression in the past year for those with a past-year MDE. “White”=White, non-Hispanic; “Black”=Black, non-Hispanic. Persons of Hispanic origin may be of any race. Suicide data for Hispanic origin should be interpreted with caution. A household’s poverty status was determined using the U.S. Census Bureau’s poverty thresholds (referred to in the figure as the “federal poverty level”). See U.S. Department of Health and Human Services, Results from the 2016 National Survey on Drug Use and Health: Detailed Tables (September 2017) and Deaths: Leading Causes for 2014, National Vital Statistics Reports, Vol. 65, Number 5 (June 2016, amended June 2017). a See Federal Interagency Forum on Child and Family Statistics, America’s Children in Brief: Key National Indicators of Well-Being, 2016 (Washington, D.C.: U.S. Government Printing Office). Page 24 GAO-18-41SP Child Well-Being Section 1: Federal Data Show That Child Well- Being Has Improved in Some Areas but Not in Others, and Children with Certain Characteristics Have Fared Worse than Others Figure 17: Alcohol, Smoking, and Drug Use Notes: For race and ethnicity data, “White”=White, non-Hispanic; “Black”=Black, non-Hispanic; “Asian”=Asian, non-Hispanic. Persons of Hispanic origin may be of any race. Illicit drugs include marijuana/hashish, cocaine (including crack), heroin, hallucinogens, inhalants, or prescription-type psychotherapeutics used nonmedically. Nonmedical use of prescription-type psychotherapeutics includes the nonmedical use of pain relievers, tranquilizers, stimulants, or sedatives and does not include over-the-counter drugs. Tobacco products include cigarettes, smokeless tobacco (i.e., snuff, dip, chewing tobacco, or “snus”), cigars, or pipe tobacco. The most recent year for which data are presented for the use of illicit drugs and nonmedical use of pain relievers is 2014, due to multiple changes in 2015 that make 2015 and 2016 data non-comparable to earlier years’ data. For more information, see U.S. Department of Health and Human Services, Substance Abuse and Mental Health Services Administration, Results from the 2016 National Survey on Drug Use and Health: Detailed Tables (September 2017). a See Federal Interagency Forum on Child and Family Statistics, America’s Children in Brief: Key National Indicators of Well-Being, 2016 (Washington, D.C.: U.S. Government Printing Office). Page 25 GAO-18-41SP Child Well-Being Section 1: Federal Data Show That Child Well- Being Has Improved in Some Areas but Not in Others, and Children with Certain Characteristics Have Fared Worse than Others Early Care and Education Early care and education of children has shown improvement or no of Children change for children overall, and children with certain characteristics fared worse, according to federal data we reviewed (see fig. 18 for the indicators we reviewed). For example, from 2005 to 2015, the estimated percentage of children enrolled in preschool stayed about the same for children overall, but Hispanic children (in 2015) and poor/near-poor children (in 2012) had lower percentages of preschool enrollment than White and non-poor children, respectively. 4 Data on student academic outcomes show that estimated average reading and math scores for students in 4th, 8th, and 12th grade generally stayed the same or slightly improved from 2005 to 2015, but average reading and math scores of Black, Hispanic, American Indian/Alaska Native (AI/AN) and poor students in these same grades were generally lower than White, Asian, and non-poor students in 2015. 5 The achievement gaps between Black and White students and between Hispanic and White students narrowed a few points in 4th and 8th grade, in part due to slightly larger average gains in Black and Hispanic scores, but stayed the same in 12th grade. The gaps between poor and non-poor students remained about the same. In addition, high school graduation rates reached an all-time high of 83 percent in 2014-15; however, rates of Black, Hispanic, AI/AN, and poor students lagged behind others. 6 Further, Black students were more likely than White students to be suspended from school for disciplinary purposes in school year 2013-14. (See figs. 19-25.) 4 In the federal data we relied on for this analysis, poor children were defined as those whose family incomes were below the U.S. Census Bureau’s poverty threshold in the year prior to data collection; near-poor children were defined as those whose family incomes ranged from the poverty threshold to 199 percent of the poverty threshold; and non-poor children were defined as those whose family incomes were at or above 200 percent of the poverty threshold. The poverty threshold is a dollar amount that varies depending on a family’s size and composition and is updated annually to account for inflation. Survey respondents were asked to select the range within which their income falls, rather than giving the exact amount of their income; therefore, the measure of poverty status is an approximation. See fig. 20. 5 For reading scores, poor students refer to those eligible for free or reduced-price school lunch, and non-poor students refer to those not eligible for free or reduced-price school lunch. For math scores, income level is measured at the school level. High-poverty schools refer to schools with 76 percent or more students eligible for free or reduced-price school lunch. Low-poverty schools refer to schools with 25 percent or fewer students eligible for free or reduced-price school lunch. 6 Poor (or economically disadvantaged) refers to students who met state criteria for classification as economically disadvantaged. Page 26 GAO-18-41SP Child Well-Being Section 1: Federal Data Show That Child Well- Being Has Improved in Some Areas but Not in Others, and Children with Certain Characteristics Have Fared Worse than Others Figure 18: Early Care and Education Indicators of Child Well-Being Page 27 GAO-18-41SP Child Well-Being Section 1: Federal Data Show That Child Well- Being Has Improved in Some Areas but Not in Others, and Children with Certain Characteristics Have Fared Worse than Others Figure 19: Cost and Quality of Child Care Notes: Cost of child care measures parents’ out-of-pocket costs for nonparental care. Cost of child care data were collected in 2012. Cost burden is calculated as the ratio of monthly household cost of care and the reported monthly income of the household in the month prior to the interview. Note that cost burden does not use the 2011 household income used for calculating the household poverty ratio. Poverty ratio is the ratio of a household’s 2011 reported income to the 2011 federal poverty threshold defined for that household’s size and age composition, using the U.S. Census Bureau’s poverty thresholds for 2011 (referred to in the figure as “federal poverty level”). Socioeconomic status was measured by a composite score based on parental education and occupations and family income. For more information, see U.S. Department of Health and Human Services, Administration for Children and Families, Office of Planning, Research, and Evaluation (OPRE), Early Care and Education Usage and Households’ Out-of-Pocket Costs: Tabulations from the National Survey of Early Care and Education (NSECE), NSECE Tabulations, OPRE Report #2016-09 (August 2016) and U.S. Department of Education, Institute for Education Sciences, National Center for Education Statistics, Digest of Education Statistics. a See U.S. Department of Health and Human Services, Office of the Assistant Secretary for Planning and Evaluation, Child Care Quality: Does it Matter and Does it Need to be Improved? (May 2000). Page 28 GAO-18-41SP Child Well-Being Section 1: Federal Data Show That Child Well- Being Has Improved in Some Areas but Not in Others, and Children with Certain Characteristics Have Fared Worse than Others Figure 20: Preschool Enrollment Notes: Preschool is defined as a group or class that is organized to provide educational experiences for children during the year or years preceding kindergarten. Data include public and private preschool. Race and ethnicity categories other than Hispanic exclude persons of Hispanic ethnicity. AI/AN=American Indian/Alaska Native. Poor children are those whose family incomes were below the U.S. Census Bureau’s poverty threshold in the year prior to data collection; near-poor children are those whose family incomes ranged from the poverty threshold to 199 percent of the poverty threshold; and non-poor children are those whose family incomes were at or above 200 percent of the poverty threshold. Survey respondents were asked to select the range within which their income falls, rather than giving the exact amount of their income, therefore, the measure of poverty status is an approximation. For more information, see U.S. Department of Education, Institute for Education Sciences, National Center for Education Statistics, Digest of Education Statistics. a See U.S. Department of Education, Strategic Plan for Fiscal Years 2014-2018. . Page 29 GAO-18-41SP Child Well-Being Section 1: Federal Data Show That Child Well- Being Has Improved in Some Areas but Not in Others, and Children with Certain Characteristics Have Fared Worse than Others Figure 21: Access to College-prep Courses and High School Graduation Rates Notes: For access to college-preparatory courses, data include public schools only. Black=Black or African American; Hispanic=Hispanic or Latino of any race; Asian/PI=Asian/Pacific Islander; and AI/AN=American Indian/Alaska Native. High/Low Black and Hispanic student enrollment refers to schools with more than 75 percent and less than 25 percent Black and Hispanic student enrollment, respectively. For more information, see U.S. Department of Education, Office for Civil Rights, 2013-2014 Civil Rights Data Collection: A First Look: Key Data Highlights on Equity and Opportunity Gaps in Our Nation’s Public Schools (Issued June 7, 2016; Revised October 28, 2016). The adjusted cohort graduation rate (ACGR) is the percentage of public high school freshman who graduate with a regular diploma within 4 years of starting 9th grade. The cohort of students entering 9th grade for the first time is “adjusted” by adding students who transfer into the cohort and subtracting students who transfer out, emigrate to another country, or die. Race and ethnicity categories other than Hispanic exclude persons of Hispanic ethnicity. Economically disadvantaged refers to students who met state criteria for this classification. For more information, see U.S. Department of Education, Institute for Education Sciences, National Center for Education Statistics, Digest of Education Statistics. a See U.S. Department of Education, Office for Civil Rights, Protecting Civil Rights, Advancing Equity: Report to the President and Secretary of Education Under Section 203(b)(1) of the Department of Education Organization Act, FY 13-14 (April 2015); U.S. Department of Education, Dear Colleague Letter on supporting access to science, technology, engineering, and math education (April 13, 2016); and Federal Interagency Forum on Child and Family Statistics, America’s Children in Brief: Key National Indicators of Well-Being, 2016 (Washington, D.C.: U.S. Government Printing Office). Page 30 GAO-18-41SP Child Well-Being Section 1: Federal Data Show That Child Well- Being Has Improved in Some Areas but Not in Others, and Children with Certain Characteristics Have Fared Worse than Others Figure 22: Reading Scores Notes: In most cases the sampling error is small enough at the scale shown that the associated 95 percent confidence intervals are not visible. Reading achievement levels: 4th grade: Basic=208, Proficient=238, Advanced=268; 8th grade: Basic=243, Proficient=281, Advanced=323; 12th grade: Basic=265, Proficient=302, Advanced=346. Race and ethnicity categories other than Hispanic exclude persons of Hispanic ethnicity. AI/AN=American Indian/Alaska Native. Asian=Asian/Pacific Islander. FRPL=Free or reduced-price lunch. Poor=eligible for FRPL. Non-poor=not eligible for FRPL. The U.S. Department of Health and Human Services’ federal poverty guidelines are used to determine eligibility for FRPL. Data include public and private schools. See U.S. Department of Education, Institute for Education Sciences, National Center for Education Statistics, Digest of Education Statistics. a See U.S. Department of Education, No Child Left Behind, Extra Credit Newsletter (2004). Page 31 GAO-18-41SP Child Well-Being Section 1: Federal Data Show That Child Well- Being Has Improved in Some Areas but Not in Others, and Children with Certain Characteristics Have Fared Worse than Others Figure 23: Math Scores Notes: In most cases the sampling error is small enough at the scale shown that the associated 95 percent confidence intervals are not visible. Math achievement levels: 4th grade: Basic=214, Proficient=249, Advanced=282; 8th grade: Basic=262, Proficient=299, and Advanced=333; 12th grade: Basic=141, Proficient=176, Advanced=216. Race and ethnicity categories other than Hispanic exclude Hispanic ethnicity. AI/AN=American Indian/Alaska Native. Asian=Asian/Pacific Islander. Data include public and private schools. High-poverty schools=schools with 76 percent or more students eligible for free or reduced-price school lunch (FRPL). Low-poverty schools=schools with 25 percent or fewer students eligible for FRPL. The U.S. Department of Health and Human Services’ federal poverty guidelines are used to determine eligibility for FRPL. See U.S. Department of Education, Institute for Education Sciences, National Center for Education Statistics, Digest of Education Statistics. a See U.S. Department of Education, National Math Panel Factsheet (2008). Page 32 GAO-18-41SP Child Well-Being Section 1: Federal Data Show That Child Well- Being Has Improved in Some Areas but Not in Others, and Children with Certain Characteristics Have Fared Worse than Others Figure 24: Student Suspensions Notes: Out-of-school suspension refers to an instance when a child is temporarily removed from a regular school setting for at least half a day for disciplinary purposes to another setting (e.g., home or behavior center). Data include public schools only. Black=Black or African American; Hispanic=Hispanic or Latino of any race; and multiracial=two or more races. Percentages are rounded to the nearest whole number. For more information, see U.S. Department of Education, Office for Civil Rights, 2013-2014 Civil Rights Data Collection: A First Look: Key Data Highlights on Equity and Opportunity Gaps in Our Nation’s Public Schools (Issued June 7, 2016; Revised October 28, 2016). a See U.S. Department of Education, Office for Civil Rights, 2013-2014 Civil Rights Data Collection, A First Look: Key Data Highlights on Equity and Opportunity Gaps in Our Nation’s Public Schools (June 2016); U.S. Department of Education, Rethink School Discipline: School District Leader Summit on Improving School Climate and Discipline, Resource Guide for Superintendent Action (Washington, D.C.: July 2015); and U.S. Department of Justice, Civil Rights Division and U.S. Department of Education, Office for Civil Rights, Dear Colleague Letter on Nondiscriminatory Administration of School Discipline (January 2014). Page 33 GAO-18-41SP Child Well-Being Section 1: Federal Data Show That Child Well- Being Has Improved in Some Areas but Not in Others, and Children with Certain Characteristics Have Fared Worse than Others Figure 25: School Crime and Safety Notes: Nonfatal victimizations include theft and violent crimes. Theft includes attempted and completed purse-snatching, completed pickpocketing, and all attempted and completed thefts, with the exception of motor vehicle thefts. Violent crimes include serious violent crimes (rape, sexual assault, robbery, and aggravated assault) and simple assault. At school includes inside the school building, on school property, and on the way to and from school. Race and ethnicity categories other than Hispanic exclude persons of Hispanic ethnicity. Due to methodological differences, use caution when comparing 2006 estimates to other years. Estimates for nonfatal victimizations of Black children and for children in households with income below $15,000 were statistically unreliable. For more information, see U.S. Department of Education, Institute for Education Sciences, National Center for Education Statistics, Digest of Education Statistics. a See Federal Interagency Forum on Child and Family Statistics, America’s Children in Brief: Key National Indicators of Well-Being, 2016. (Washington, D.C.: U.S. Government Printing Office). Page 34 GAO-18-41SP Child Well-Being Section 2: Experts Noted Several Considerations Section 2: Experts Noted Several Considerations for Policymakers Seeking to Address the Multiple Dimensions of Child Well- for Policymakers Seeking to Address the Multiple Being Dimensions of Child Well-Being We discussed with experts from 18 organizations, who represent a range of viewpoints, several areas that policymakers could consider when seeking to address the multiple dimensions of child well-being: (1) considering the whole family; (2) focusing on the early years of childhood and adolescence; (3) considering the appropriateness of both targeted and universal interventions; (4) evaluating the effect of policy interventions and fostering innovation; and (5) coordinating among federal, state, local, and non-governmental entities (see app. III for a list of the organizations). As evidenced by our discussion above, child well- being may be measured across multiple indicators that reflect many areas of a child’s life. However, according to the experts we consulted, as policymakers and practitioners work to improve child well-being, they need to consider that the various areas are interconnected and that the challenges children face in one area may significantly impact other aspects of their lives. For example, being homeless can negatively affect a child’s mental health and academic achievement. Similarly, living in poverty affects not only the material resources of a family, but also negatively impacts the neighborhood in which they live, which can affect a child’s safety. When poverty affects a child’s health, the family’s financial resources may be further strained given the costs of health care, thus exacerbating the negative effects of living in poverty. Considering the Whole Experts we consulted from organizations who represent a range of Family viewpoints suggested that policymakers consider ways to support a family’s ability to provide the safe, supportive, and nurturing environment that children need, as a child’s needs are intimately associated with those of their parents. They identified a range of strategies that recognize the critical role families play in ensuring child well-being. For example, the experts said that access to decent, stable, and affordable housing—one of a family’s greatest needs—can positively influence a child’s school readiness and health and reduce the risk of maltreatment. Among the many ways identified by the experts to support family stability, including through policies that support work, asset building, and wealth creation, some experts highlighted the role of policies that promote marriage or encourage the maintenance of two-income households. They suggested that children in married or two-income households generally have greater access to the financial and non-financial resources (e.g., parental support) that are important to child well-being. Experts also discussed approaches designed to address the needs of children and parents at the same time—so-called two-generation approaches. As an example, Head Start programs provide early Page 35 GAO-18-41SP Child Well-Being Section 2: Experts Noted Several Considerations for Policymakers Seeking to Address the Multiple Dimensions of Child Well- Being education services to low-income children while offering support to families, such as services that promote housing stability, continued education, and financial security, according to some experts. 1 The experts said that involving parents in such interventions is especially important in maximizing the positive effects for children. In addition, they cited the need to involve parents in nutrition interventions for children, as parents are the ones who choose which foods to bring into the home. They provided the example of the Summer Electronic Benefits Transfer for Children program as one that addresses food insecurity for children whose families may not be able to provide sufficient food in the summer months. 2 Similarly, according to experts, parents should be partners in mental health interventions for their children. One such model that they said has shown positive results, known as Functional Family Therapy, brings the family into the process by coaching them on how to respond to youth who may be involved in delinquent or criminal behavior without the youth becoming more involved in the juvenile justice system. 3 To help identify the particular needs of children and their families, the experts we spoke to identified various entry points to screen children and families for needed services, such as early childhood education programs, K-12 schools, and primary health care visits. However, experts suggested that trying to ensure that such screenings are done routinely through these entities is difficult; for example, such screenings can be disruptive to typical health care settings and are costly. Experts further noted that interventions that address the needs of children and parents should be considered as part of a multi-faceted approach to address the adverse impact of poverty. For example, experts from one organization discussed the importance of health insurance to help treat 1 Head Start promotes the school readiness of young children from low-income families through agencies in their local community. Head Start and Early Head Start programs support the comprehensive development of children from birth to age 5, in centers and schools, child care partner locations, and in their own homes. Head Start services include services to support early learning, health, and family well-being. 2 The Summer Electronic Benefits Transfer for Children program is a demonstration grant to states that provides families with children eligible for free and reduced-price school meals access to additional food benefits during the summer. 3 According to the U.S. Department of Justice, although commonly used as an intervention program, the model is also an effective prevention program for at-risk adolescents and their families. Whether implemented as an intervention or a prevention program, it may include diversion, probation, alternatives to incarceration, and/or reentry programs for youth returning to the community following release from a high-security, severely restrictive institutional setting. Page 36 GAO-18-41SP Child Well-Being Section 2: Experts Noted Several Considerations for Policymakers Seeking to Address the Multiple Dimensions of Child Well- Being maternal depression, which is prevalent in families with infants living in poverty and negatively affects the well-being of all children in the family. Experts also said that stress and the scarcity of resources associated with poverty affect the ability of parents to cope with challenges, and make it harder for these parents to manage everyday tasks and responsibilities. Moreover, low-income families generally have fewer supports than higher income families, such as paid leave that can support a parent’s ability to stay home with a sick child. In another example, experts recognized the challenges children face in high-poverty neighborhoods—such as access to poorer quality schools and fewer neighborhood amenities—and a few identified school choice as an important option that attempts to break the link between a child and the challenges associated with attending a high- poverty school. Focusing on the Early While experts varied in the specific interventions they recommended, Years and Adolescence those we spoke to indicated that the earlier an intervention occurs, the better for the child, as a child’s early years are critical to their development. Additionally, as previously described, they said that interventions are often particularly effective when they involve parents. For example, experts from one organization described a home visiting program in which nurses visit parents and their newborn children during the first few weeks of the child’s life, with the goal of connecting parents with the community resources they need to raise a healthy child. As part of the program, nurses provide in-home health assessments of mothers and newborns and discuss the social conditions that affect the new family. According to the experts, the program has shown positive effects, including effects on parenting behaviors and father involvement, as well as reduced rates of infant hospitalization. Moreover, challenges children face can have cumulative effects on their well-being. For example, experts from one organization explained that challenges children may have at birth shape their ability to exhibit self- control. Children with a lack of self-control may be more likely to be suspended or expelled from school and to come into contact with the juvenile justice and prison systems later in life, according to these experts. In another example, experts noted that poverty can negatively affect brain development in children and lead to measurable gaps in language acquisition by 18 months of age and educational delays that are evident as a child reaches school age. More generally, according to experts, impacts from early investments can last for years, such as through improved educational outcomes, reduced special education Page 37 GAO-18-41SP Child Well-Being Section 2: Experts Noted Several Considerations for Policymakers Seeking to Address the Multiple Dimensions of Child Well- Being costs, reduced contact with the juvenile justice system, and higher employment earnings. While experts said interventions ideally take place early in a child’s life, they also noted the importance of intervening with children of all ages. While much is known about early childhood development, one expert noted that less is known about what promotes the well-being of children ages 8-18 years. They said that interventions during adolescence may be particularly important, considering the continued brain development that occurs as social and peer pressures emerge. For example, adolescents may deal with a host of new challenges, including the stress of college admissions, avoiding unwanted pregnancy, and access to drugs. Further, experts we consulted suggested that interventions need to consider a child’s developmental stage. For example, according to experts from one organization, while poverty generally has the greatest impact in early childhood, housing instability tends to affect children the most during the pre-teen years. Meanwhile, children may be more influenced by their peers at this age and less inclined to seek services recommended or initiated by their parents, such as mental health counseling. Experts from another organization identified various interventions with positive effects for students in high school, including requiring students to take a college admissions test, which they said was shown to increase the number of children from poor households going to college. In another example, they cited a program for at-risk male youth that provides school-based counseling, mentoring, educational enrichment, and anger management training, and has been shown to increase school engagement and performance and decrease student violence and arrests. Relatedly, because challenges to child well-being are interrelated, experts said that interventions in one area have effects in others. For example, if child maltreatment is reduced, so, too, is the need for mental health care. Considering the Both targeted and universal interventions may be appropriate to address Appropriateness of Both child well-being, depending on various factors, according to the experts we consulted. Those representing a range of viewpoints generally agreed Targeted and Universal that scarce resources should be targeted to the most vulnerable children Interventions with the greatest need, since it is not cost-effective to provide services to those who would otherwise be able to pay for them. Poverty, as we have discussed, is detrimental to child well-being in myriad ways, as it underlies most child well-being challenges, makes them worse, and limits a child’s opportunities for upward mobility. Experts from one organization said that evidence suggests targeted interventions, such as those that may help alleviate the effects of poverty, provide the most benefit. Page 38 GAO-18-41SP Child Well-Being Section 2: Experts Noted Several Considerations for Policymakers Seeking to Address the Multiple Dimensions of Child Well- Being However, programs for the poor risk isolating and stigmatizing high-need families and may compromise program quality by excluding higher- income children whose parents are in a position to demand quality, experts cautioned. While universal programs may cost more, they offer other benefits, according to some experts: They can be easier to access, allow low-income children to interact with peers across income levels, and may have broader political appeal (e.g., universal pre-k versus early education programs for low-income children), among others. Some experts identified policies they think should be universal. For example, experts from one organization suggested that school choice programs (including education savings accounts) be universally available to allow families to make their own decisions about which schools their children should attend. 4 In another example, experts said it is important to not differentiate interventions based on income for children in child welfare and juvenile justice systems, as all children in these systems should be considered vulnerable, regardless of their family income. Rather than having to choose between targeted and universal approaches, interventions may combine aspects of the two. For example, experts noted that one state’s paid family leave policy, while broadly available, was changed to enable greater take-up by low-income families. 5 Additionally, universal programs that have fees based on a sliding scale can be accessible to all and allow families to pay according to their incomes. Evaluating the Effect of In designing interventions for child well-being, experts suggested there is Policy Interventions and an important role for both evaluation and innovation. They generally agreed that implementing evidence-based practices is essential to Fostering Innovation effectively address child well-being, and noted that randomized controlled trials, which are designed to isolate the effects of a particular intervention on a population, are the “gold standard” of evaluation. 6 At the same time, 4 Education savings accounts are state programs that provide public funds that eligible students may use for a broad set of educational expenses, such as private school tuition and fees, online learning programs, private tutoring, education therapies, or higher education expenses, depending on the program. 5 Recent changes to this state’s law increased the wage replacement rate under the state unemployment compensation disability law and the family temporary disability insurance program, based on the worker’s wages, effective beginning 2018. 6 Randomized controlled trials assign people, at random, to participate in a program or serve as a control group in order to compare outcomes for a program’s participants with the outcomes comparable people achieve without the program. Page 39 GAO-18-41SP Child Well-Being Section 2: Experts Noted Several Considerations for Policymakers Seeking to Address the Multiple Dimensions of Child Well- Being however, some experts noted that few interventions are evaluated using the high standard of randomized trials and identified challenges to the use of randomized trials for interventions that affect children; for example, they noted that it is unethical to provide benefits, such as food assistance or health insurance coverage, to a random selection of children that excludes others who also need these services. Experts said that these trials are expensive and may not always be well-suited to evaluate interventions for families with complex needs and circumstances that may require combined or sequenced interventions. It may also take a long time—sometimes years—for outcomes to be realized from interventions that can affect child well-being. Experts noted that policies aimed at prevention, for example, do not see immediate impacts. In light of such challenges, experts offered alternatives to randomized controlled trials, such as rapid-cycle evaluations and quasi-experimental methods. 7 One expert noted that the desire for perfect data should not be the enemy of using good data. Experts also discussed how innovation may help build evidence about the effectiveness of interventions, given the difficulties noted above. Evaluations can help demonstrate the effectiveness of an intervention for a specific case or group; however, developing innovative ways to implement an intervention may demonstrate how it can work in different contexts, such as when an intervention is scaled to a larger population, or when a service provider faces challenges with limited staff, time, or funding for implementation. Experts suggested that introducing innovations is also important to understanding how to tailor evidence- based practices to certain populations for whom evidence is lacking (e.g., racial and ethnic minorities). Innovations that allow results to be put into 7 Rapid-cycle evaluations use behavioral sciences to improve and assess program and policy impact and are generally of a low-cost, iterative nature. See The White House Office of Social Innovation and Civic Participation, Find What Works, downloaded from https://obamawhitehouse.archives.gov/administration/eop/sicp/initiatives/find-what-works on June 26, 2017 and Baird, Peter, Dan Cullinan, Patrick Landers, and Leigh Reardon (2016), Nudges for Child Support: Applying Behavioral Insights to Increase Collections. OPRE Report 2016-01. Washington, D.C.: Office of Planning, Research and Evaluation, Administration for Children and Families, U.S. Department of Health and Human Services. Quasi-experimental comparison group design is employed by impact evaluations due to the difficulties in establishing a random process for assigning units of study to a program as well as the opportunity provided when only a portion of the targeted population is exposed to the program. This design also uses a treatment group and one or more comparison groups; however, unlike the groups in a true experiment, membership in these groups is not randomly assigned. See GAO, Designing Evaluations: 2012 Revision, GAO-12-208G (Washington, D.C.: January 2012). Page 40 GAO-18-41SP Child Well-Being Section 2: Experts Noted Several Considerations for Policymakers Seeking to Address the Multiple Dimensions of Child Well- Being practice quickly provide opportunities for policy to continuously improve, according to one expert. Experts from another organization said that sharing promising practices and lessons learned from innovating, including those that did not work, contributes to “practice-based evidence.” Citing tiered funding for a federal home visiting program that supports innovative and promising practices, some experts also said that program funding can foster innovation. With such variations in evidence, a few experts suggested the term “evidence-based” be further defined or expanded; however, one expert cautioned that the term was prone to overuse and that there is a tendency to call practices “evidence-based” regardless of whether evidence exists. Coordinating among Experts we interviewed had different views on the role of government in Federal, State, Local, and addressing child well-being, but several experts said efforts to address the complex nature of child well-being are hindered by insufficient Non-Governmental coordination at the federal level. More specifically, while experts provided Entities some examples of federal coordination, such as in addressing education or disconnected youth, they said federal agencies generally operate in siloes and lack the multidisciplinary structure needed for a coordinated approach for child well-being. They said these siloes result in challenges such as multiple agencies addressing similar child well-being issues, disparate data that are difficult to share, and incompatible agency definitions. Looking across programs that affect the well-being of children, youth, and families, and finding ways to hold agencies accountable for working together on related issues is important to improve child well- being, experts said. Further, some experts noted that it would be valuable for the federal government to consider its investment in children in comparison to other subpopulations, such as seniors. Experts also discussed the importance of federal agencies coordinating with stakeholders at other governmental levels and outside the government. One expert noted that health and human service agencies are not the only entities needed to address child well-being and suggested that community stakeholders work together to determine what resources are needed for the children in their community. State and local agencies may be better positioned to meet the needs of their communities, according to experts we consulted, who pointed to some promising local practices. For example, experts from one organization mentioned a school district that added a question to its enrollment form to help identify uninsured children who were eligible for health insurance coverage. In another example, some local areas use a case management entity to coordinate the needs of children and families across various Page 41 GAO-18-41SP Child Well-Being Section 2: Experts Noted Several Considerations for Policymakers Seeking to Address the Multiple Dimensions of Child Well- Being agencies that may include juvenile justice, special education, and social services. Experts from one organization said that because some federal programs are administered through states, coordination across programs at the state level is important. Experts also emphasized the need to involve families, advocates, and non-governmental policy experts in such work. However, we also heard that challenges faced by states and localities, such as the limited capacity of service providers, limited funding, restrictions on data sharing, and the lack of dissemination of promising practices, constrain progress toward improving child well-being. Some of the experts we consulted provided suggestions for how the federal government could help address some of these challenges and improve its efforts to increase child well-being. More specifically, they said the federal role is important to: • define child well-being and set federal minimum standards, or benchmarks, in various areas, including housing, health, and education; • align child well-being goals and outcomes across programs and hold agencies accountable for working together, which can be particularly important as the benefits of investments in some systems, such as housing, may be reaped elsewhere, such as improvements in health; • collect and disseminate data, including to identify child well-being disparities and analyze the causes, as well as provide leadership for data sharing efforts; • support evaluation and research related to child well-being issues; • support civil rights and equity for children, including through fair housing programs; and • provide funding, training, and technical assistance to states and localities related to child well-being issues. Other experts, however, offered contrasting views on the federal role. Some questioned what they saw as federal overreach in a few of these areas and noted the importance of determining whether federal action is warranted or appropriate. For example, one expert suggested that the federal government has limited authority to intervene with education, aside from its responsibility to ensure that states and school districts provide equitable educational opportunities. Experts from another organization said the federal government should help families help themselves by supporting work, rather than supplanting or displacing it with federal assistance. In that way, they said, the federal government Page 42 GAO-18-41SP Child Well-Being Section 2: Experts Noted Several Considerations for Policymakers Seeking to Address the Multiple Dimensions of Child Well- Being could supplement the needs of families who are working but still cannot make ends meet. The GPRA Modernization Act of 2010 requires OMB to coordinate with agencies to develop federal government priority goals (known as cross- agency priority or CAP goals). 8 These are long-term, outcome-oriented goals that cover a limited number of crosscutting policy areas. According to OMB, these goals are identified in areas where increased cross- agency collaboration on outcome-focused areas is likely to improve progress. Prior CAP goals have addressed areas such as education and the workforce, including a goal designed to improve Science, Technology, Engineering, and Mathematics (STEM) Education. 9 The Act also requires that agency strategic plans include a description of how agency goals and objectives contribute to the cross-agency priority goals, and how agencies are working with each other to achieve these cross-agency priority goals. For example, as part of an effort to expand the impact of existing federal STEM education programs, the STEM Education Strategic Plan has been incorporated into a CAP goal since 2014, according to the Executive Office of the President’s Office of Science and Technology Policy. 10 This step institutionalizes the STEM Education Strategic Plan through agency performance metrics and requires agencies to issue public implementation updates every quarter. The current priority goals cover the period from 2014-2018. To date, child well-being has not been designated as a CAP goal. OMB is reviewing the current administration’s priorities to help develop the next set of CAP goals. OMB officials told us they expect to issue the next set of goals with the release of the fiscal year 2019 budget. By highlighting child well-being as an overarching priority area, and ensuring that this priority is reflected in agencies’ 8 The GPRA Modernization Act of 2010 established a new framework aimed at encouraging a more crosscutting and integrated approach to improving government performance, including processes to improve transparency and accountability. Pub. L. No. 111-352, 124 Stat. 3866 (2011). GPRAMA enhanced the Government Performance and Results Act of 1993 (GPRA), Pub. L. No. 103-62, 107 Stat. 285 (1993). 9 CAP goals also include goals for management improvements needed across the federal government, including financial management, human capital management, information technology management, procurement and acquisition management, and real property management. At a minimum, CAP goals are to be updated or revised every four years. See a recent GAO report for a discussion on the implementation of the GPRA Modernization Act, including a discussion on selected CAP goals, GAO-16-509 (Washington, D.C.: May 20, 2016). 10 Executive Office of the President, Office of Science and Technology Policy, Progress Report on Coordinating Federal Science, Technology, Engineering, and Mathematics (STEM) Education. (Washington, D.C.: March 31, 2016). Page 43 GAO-18-41SP Child Well-Being Section 2: Experts Noted Several Considerations for Policymakers Seeking to Address the Multiple Dimensions of Child Well- Being strategic plans, OMB could help draw needed attention to improve collaboration among federal efforts to enhance child well-being. Fostering the well-being of the nation’s children requires attention to a Conclusions multiplicity of interrelated factors that can contribute to child well-being and the role that families, communities, governmental and non- governmental organizations play in caring for these children. Appropriate interventions that address the needs of children can help them become responsible and productive adults who, in turn, contribute to the viability of the nation’s social and economic sectors. Despite sustained efforts to improve the well-being of children, including those from economically disadvantaged families, some indicators have shown little improvement over the time period covered by the data in this report, and significant gaps between groups remain. For its part, the federal government funds and administers programs that are designed to improve the well-being of children and families, collects a range of data on various indicators of child well-being, and sponsors and conducts related research and evaluations, among other things. However, several experts noted that federal agencies tend to focus narrowly on their own mission and that there is not a coordinated federal approach for addressing child well- being. OMB is currently revising the federal government’s priority goals (cross-agency priority or CAP goals) and expects to issue the next set of 4-year CAP goals with the fiscal year 2019 budget. A coordinated federal approach to child well-being, such as through a CAP goal, and subsequent agency strategic plans that describe how their goals and objectives contribute to the CAP goals, could provide the federal government an opportunity to better address the needs of children and families in ways that take into account the interrelatedness of federal actions and policies that aim to improve child well-being. GAO recommends that the Director of OMB consider developing a goal Recommendation for that addresses a coordinated federal approach to child well-being among Executive Action its next set of cross-agency priority (CAP) goals, including working with relevant agencies to ensure their strategic plans include goals and objectives related to the CAP goal. (Recommendation 1) We provided a draft of this report to the Office of Management and Agency Comments Budget (OMB) for review and comment. OMB staff provided us with oral comments and neither agreed nor disagreed with our recommendation that the agency consider developing a goal that addresses a coordinated Page 44 GAO-18-41SP Child Well-Being Section 2: Experts Noted Several Considerations for Policymakers Seeking to Address the Multiple Dimensions of Child Well- Being federal approach to child well-being among its next set of cross-agency priority (CAP) goals. OMB staff reiterated that the agency is currently in the process of developing its next set of CAP goals, which are usually reserved for a limited set of priorities, and expects to announce these goals concurrent with the fiscal year 2019 budget. As part of the process, agency staff said they consult relevant Congressional committees and other stakeholders. OMB staff also provided technical comments, which we incorporated as appropriate. Page 45 GAO-18-41SP Child Well-Being Appendix I: Scope and Methodology Appendix I: Scope and Methodology The objectives of this report were to examine (1) what is known about the state of child well-being in the United States and how it has changed in recent years, and (2) experts’ views on what policymakers could consider when addressing child well-being. To address our objectives, we selected several indicators of child well-being based on our review of child well- being frameworks, reviewed federal data, and interviewed agency officials and a variety of subject matter experts about child well-being issues. We reviewed 16 frameworks of child well-being indicators developed and Review of Child Well- published by several domestic and international organizations and Being Frameworks researchers, and a federal inter-agency group (see app. II for a list of selected organizations and frameworks). Based on this review, and after discussing these indicators with a variety of subject matter experts, we selected and categorized indicators along the following areas of a child’s life: (1) family, physical, and social environment, (2) physical and mental health, and (3) early care and education. (See fig. 2.) For each child well-being indicator, we reviewed published federal data Review of Federal for children over the most recent 10-year period, and by certain Datasets characteristics—race/ethnicity, income level/poverty status, and family composition—for the first and last year of this 10-year period, to the extent data were available. Based on our review of data, we identified and reported trends over time for children overall and any differences between children with certain characteristics, including whether differences persisted, narrowed, or widened. Data were not consistently available for every child well-being indicator over the most recent 10 years or by each of these characteristics; as a result we report information for only those years for which data were available. Many of the data sources from which estimates were drawn are federal statistical surveys. For data that came from a statistical source, we reviewed the source agency’s technical documentation for the survey. When the source publication did not provide the confidence interval for an estimate, we implemented agency technical guidance to calculate the 95 percent confidence interval using the published weighted standard error. All national estimates produced from federal probability survey data are subject to sampling errors. We express our confidence in the precision of the results as a 95 percent confidence interval. This is the interval that would contain the actual population value for 95 percent of the samples the respective agency could have drawn. We assessed the reliability of the data by (1) reviewing existing information about the data Page 46 GAO-18-41SP Child Well-Being Appendix I: Scope and Methodology and the system that produced them and, in some cases, (2) interviewing agency officials knowledgeable about the data. We determined that the data we reported were sufficiently reliable for the purposes of this report. For some indicators, data were not available for children for race/ethnicity, household income, and family composition. Additionally, the sub-group categories of children we reported on were not always an exhaustive list of those available in the federal data. We interviewed federal agency officials from the U.S. Office of Interviews with Management and Budget (OMB), the Department of Agriculture’s Federal Officials and Economic Research Service, the Department of Education’s National Center for Education Statistics, the Department of Health and Human Child Well-Being Services’ (HHS) Centers for Disease Control and Prevention, and HHS’s Experts Assistant Secretary for Planning and Evaluation about child well-being issues and related data. During these interviews, we asked agency officials about indicators of the well-being of children in the United States, federal data collected on these indicators, and federal efforts to address child well-being. With OMB officials, we also discussed their views on the cross-agency priority goals and the benefits to federal agencies and program areas of identifying specific areas, such as child well-being, as a priority goal. We also interviewed officials from 18 non-governmental organizations that conduct research and activities related to children and families to obtain a range of perspectives on what policymakers should consider when addressing child well-being. We selected organizations to obtain balance and coverage across three criteria: (1) subject matter expertise, (2) a range of viewpoints, including perspectives on the role of the federal government, and (3) type of organization. Specifically, we included groups that had expertise on issues related to children’s family, physical, and social environment; physical and mental health; and early care and education. We included nonprofit, academic, and advocacy groups and reviewed published material from organizations’ websites to help inform our selection. We used semi-structured questions to obtain experts’ perspectives on the (1) child well-being indicators we selected, (2) need for any interventions to improve child well-being, and if so, (3) timing, type, and evaluation of interventions, and (4) role of federal, state, local, and private entities, if any, in interventions. We reported the results of our expert interviews to reflect the full range of perspectives, and identified areas of consensus and variation among expert views where appropriate. The information and perspectives we obtained and present in this report should not be regarded as an exhaustive discussion of all viewpoints of Page 47 GAO-18-41SP Child Well-Being Appendix I: Scope and Methodology these experts on child well-being issues; nor is it generalizable to all child welfare experts. The viewpoints summarized in this report also do not necessarily represent the views of all the experts we interviewed, their organizations, or GAO. We provided a draft of this report for review to two external experts who are members of the Comptroller General’s Advisory Board. The board is comprised of individuals with broad expertise in public policy and provides advice to GAO. We incorporated their comments throughout the report, as appropriate. We conducted this performance audit from March 2016 to November 2017 in accordance with generally accepted government auditing standards. Those standards require that we plan and perform the audit to obtain sufficient, appropriate evidence to provide a reasonable basis for our findings and conclusions based on our audit objectives. We believe that the evidence obtained provides a reasonable basis for our findings and conclusions based on our audit objectives. Page 48 GAO-18-41SP Child Well-Being Appendix II: Selected Child Well-Being Appendix II: Selected Child Well-Being Frameworks Frameworks Adamson, Peter. Child Poverty in Perspective: An Overview of Child Well- Being in Rich Countries, Innocenti Report Card 7. Florence, Italy: UNICEF Innocenti Research Centre, 2007. Ben-Arieh, Asher. “Measuring and monitoring the well-being of young children around the world.” Paper commissioned for the Education for All Global Monitoring Report 2007: Strong foundations: early childhood care and education, 2006. Chapple, Simon, and Dominic Richardson. “Comparative Child Well-being across the OECD.” Doing Better for Children, chapter 2. OECD, 2009. Child Trends. Child Trends Data Bank. Bethesda, MD: Child Trends. Accessed on April 14, 2016. https://www.childtrends.org/databank-indicators/databank-by-life-stage/. Child Trends. Child Well-Being: Indicator List for Child Well-Being. Bethesda, MD: Child Trends. Accessed on April 14, 2016. https://www.childtrends.org/databank-indicators/databank-by-topics/. Children’s Defense Fund. The State of America’s Children 2014. Washington D.C.: Children’s Defense Fund, 2014. Diversitydatakids.org. Waltham, MA: The Heller School for Social Policy and Management at Brandeis University. Accessed on April 15, 2016. http://www.diversitydatakids.org/. Federal Interagency Forum on Child and Family Statistics. America’s Children in Brief: Key National Indicators of Well-Being, 2016. Washington, D.C.: U.S. Government Printing Office, July 2016. Fernandes, Liliana, Américo Mendes, and Aurora Teixeira. “A Weighted Multidimensional Index of Child Well-Being Which Incorporates Children’s Individual Perceptions.” Social Indicators Research, vol. 114, 2013. Gutierrez, Florencia, and Laura Speer. 2016 KIDS COUNT Data Book: State Trends in Child Well-Being. Baltimore, MD: The Annie E. Casey Foundation, 2016. Healthy People 2020 Leading Health Indicators. Accessed on November 25, 2016. https://www.healthypeople.gov/2020/Leading-Health-Indicators. Page 49 GAO-18-41SP Child Well-Being Appendix II: Selected Child Well-Being Frameworks Land, Kenneth C., Child and Youth Well-Being Index (CWI) Report (2014). Duke University Center for Child and Family Policy, 2014. Land, Kenneth C., Vicki L. Lamb, Sarah O. Meadows, et al. “Measuring trends in child well-being: an evidence-based approach.” Social Indicators Research, vol. 80, no. 1, 2007. Lippman, Laura H., Kristin Anderson Moore, and Hugh McIntosh. Positive Indicators of Child Well-Being: A Conceptual Framework, Measures and Methodological Issues, Innocenti Working Paper No. 2009-21. Florence, Italy: UNICEF Innocenti Research Centre, 2009. Moore, Kristin A., David Murphey, and Tawana Bandy. “Positive Child Well-Being: An Index Based on Data for Individual Children.” Maternal and Child Health Journal, vol.16, no. 1, 2012. Stagner, Matthew, Robert Goerge, and Pete Ballard. Improving Indicators of Child Well-Being. Chicago, IL: Chapin Hall at the University of Chicago, 2009. Page 50 GAO-18-41SP Child Well-Being Appendix III: List of Expert Organizations Appendix III: List of Expert Organizations American Enterprise Institute American Psychological Association American Public Human Services Association The Annie E. Casey Foundation The Brookings Institution Cato Institute Center for Child and Family Policy at Duke University Center for Law and Social Policy Chapin Hall at the University of Chicago Child Trends Children’s Defense Fund Georgetown University Center for Children and Families The Heritage Foundation MacArthur Foundation Mathematica Policy Research National Center for Missing & Exploited Children The Pew Charitable Trusts Urban Institute Page 51 GAO-18-41SP Child Well-Being Appendix IV: Related GAO Products Appendix IV: Related GAO Products Family, Physical, and Federal Low-Income Programs: Eligibility and Benefits Differ for Selected Social Environment Programs Due to Complex and Varied Rules. GAO-17-558. Washington, D.C.: June 29, 2017. Foster Care: HHS Has Taken Steps to Support States’ Oversight of Psychotropic Medications, but Additional Assistance Could Further Collaboration. GAO-17-129. Washington, D.C.: January 5, 2017. Supplemental Nutrition Assistance Program: More Information on Promising Practices Could Enhance States’ Use of Data Matching for Eligibility. GAO-17-111. Washington, D.C.: October 19, 2016. Foster Care: Most Tribes Do Not Anticipate Challenges with Case Goal Changes, but HHS Could Further Promote Guardianship Assistance. GAO-16-625. Washington, D.C.: August 8, 2016. Supplemental Nutrition Assistance Program: Policy Changes and Calculation Methods Likely Affect Improper Payment Rates, and USDA Is Taking Steps to Help Address Recipient Fraud. GAO-16-708T. Washington, D.C.: July 6, 2016. Supplemental Nutrition Assistance Program: Enhanced Detection Tools and Reporting to Combat Recipient Fraud Are in Development. GAO-16-719T. Washington, D.C.: June 9, 2016. Unaccompanied Children: HHS Should Improve Monitoring and Information Sharing Policies to Enhance Child Advocate Program Effectiveness. GAO-16-367. Washington, D.C.: April 19, 2016. Emergency Management: Improved Federal Coordination Could Better Assist K-12 Schools Prepare for Emergencies. GAO-16-144. Washington, D.C.: March 10, 2016. Unaccompanied Children: HHS Can Improve Monitoring of Their Care. GAO-16-429T. Washington, D.C.: February 23, 2016. Temporary Assistance for Needy Families: Update on States Counting Third-Party Expenditures toward Maintenance of Effort Requirements. GAO-16-315. Washington, D.C.: February 10, 2016. Unaccompanied Children: HHS Can Take Further Actions to Monitor Their Care. GAO-16-180. Washington, D.C.: February 5, 2016. Page 52 GAO-18-41SP Child Well-Being Appendix IV: Related GAO Products Electronic Monitoring: Draft National Standard for Offender Tracking Systems Addresses Common Stakeholder Needs. GAO-16-10. Washington, D.C.: October 26, 2015. Foster Care: HHS Could Do More to Support States’ Efforts to Keep Children in Family-Based Care. GAO-16-85. Washington, D.C.: October 9, 2015. Child Welfare: Steps Have Been Taken to Address Unregulated Custody Transfers of Adopted Children. GAO-15-733. Washington, D.C.: September 16, 2015. School Nutrition: USDA Has Efforts Underway to Help Address Ongoing Challenges Implementing Changes in Nutrition Standards. GAO-15-656. Washington, D.C.: September 14, 2015. Federal Low-Income Programs: Multiple Programs Target Diverse Populations and Needs. GAO-15-516. Washington, D.C.: July 30, 2015. Unaccompanied Alien Children: Actions Needed to Ensure Children Receive Required Care in DHS Custody. GAO-15-521. Washington, D.C.: July 14, 2015. Youth Athletes: Sports Programs’ Guidance, Practices, and Policies to Help Prevent and Respond to Sexual Abuse. GAO-15-418. Washington, D.C.: May 29, 2015. Domestic Food Assistance: Multiple Programs Benefit Millions of Americans, but Additional Action Is Needed to Address Potential Overlap and Inefficiencies. GAO-15-606T. Washington, D.C.: May 20, 2015. School-Meals Programs: Additional Verification Could Help USDA Ensure Legitimate Access. GAO-15-594T. Washington, D.C.: May 7, 2015. Victims of Child Abuse Act: Further Actions Needed to Ensure Timely Use of Grant Funds and Assess Grantee Performance. GAO-15-351. Washington, D.C.: April 29, 2015. Foster Care: HHS Needs to Improve the Consistency and Timeliness of Assistance to Tribes. GAO-15-273. Washington, D.C.: February 25, 2015. Page 53 GAO-18-41SP Child Well-Being Appendix IV: Related GAO Products Nutrition Assistance: Additional Guidance Could Assist States in Reducing Risk of Online Sale of Infant Formula. GAO-15-94. Washington, D.C.: December 11, 2014. Temporary Assistance for Needy Families: Action Is Needed to Better Promote Employment-Focused Approaches. GAO-15-31. Washington, D.C.: November 19, 2014. Sex Offender Registration and Notification Act: Additional Outreach and Notification of Tribes about Offenders Who Are Released from Prison Needed. GAO-15-23. Washington, D.C.: November 18, 2014. Foster Children: HHS Could Provide Additional Guidance to States Regarding Psychotropic Medications. GAO-14-651T. Washington, D.C.: May 29, 2014. Foster Care: HHS Needs to Improve Oversight of Fostering Connections Act Implementation. GAO-14-347. Washington, D.C.: May 29, 2014. Foster Children: Additional Federal Guidance Could Help States Better Plan for Oversight of Psychotropic Medications Administered by Managed-Care Organizations. GAO-14-362. Washington, D.C.: April 28, 2014. School Lunch: Implementing Nutrition Changes Was Challenging and Clarification of Oversight Requirements Is Needed. GAO-14-104. Washington, D.C.: January 28, 2014. Child Welfare: Federal Agencies Can Better Support State Efforts to Prevent and Respond to Sexual Abuse by School Personnel. GAO-14-42. Washington, D.C.: January 27, 2014. WIC Program: Improved Oversight of Income Eligibility Determination Needed. GAO-13-290. Washington, D.C.: February 28, 2013. Registered Sex Offenders: Sharing More Information Will Enable Federal Agencies to Improve Notifications of Sex Offenders’ International Travel. GAO-13-200. Washington, D.C.: February 14, 2013. Sex Offender Registration and Notification Act: Jurisdictions Face Challenges to Implementing the Act, and Stakeholders Report Positive and Negative Effects. GAO-13-211. Washington, D.C.: February 7, 2013. Page 54 GAO-18-41SP Child Well-Being Appendix IV: Related GAO Products Supplemental Nutrition Assistance Program: Improved Oversight of State Eligibility Expansions Needed. GAO-12-670. Washington, D.C.: July 26, 2012. Supplemental Security Income: Better Management Oversight Needed for Children’s Benefits. GAO-12-497. Washington, D.C.: June 26, 2012. Homelessness: To Improve Data and Programs, Agencies Have Taken Steps to Develop a Common Vocabulary. GAO-12-302T. Washington, D.C.: December 15, 2011. TANF and Child Welfare Programs: Increased Data Sharing Could Improve Access to Benefits and Services. GAO-12-2. Washington, D.C.: October 7, 2011. Domestic Violence, Sexual Assault, Dating Violence, and Stalking: National Data Collection Efforts Underway to Address Some Information Gaps. GAO-11-833T. Washington, D.C.: July 13, 2011. Missing Children: DOJ Could Enhance Oversight to Help Ensure That Law Enforcement Agencies Report Cases in a Timely Manner. GAO-11-444. Washington, D.C.: June 21, 2011. Combating Child Pornography: Steps Are Needed to Ensure That Tips to Law Enforcement Are Useful and Forensic Examinations Are Cost Effective. GAO-11-334. Washington, D.C.: March 31, 2011. Physical and Mental Newborn Health: Federal Action Needed to Address Neonatal Abstinence Health Syndrome. GAO-18-32. Washington, D.C.: October 4, 2017. Pediatric Trauma Centers: Availability, Outcomes, and Federal Support Related to Pediatric Trauma Care. GAO-17-334. Washington, D.C.: March 27, 2017. Federal Autism Activities: Agencies Are Encouraging Early Identification and Providing Services, and Recent Actions Could Improve Coordination. GAO-16-446. Washington, D.C.: May 20, 2016. Medicaid and CHIP: Increased Funding in U.S. Territories Merits Improved Program Integrity Efforts. GAO-16-324. Washington, D.C.: April 8, 2016. Page 55 GAO-18-41SP Child Well-Being Appendix IV: Related GAO Products Provider Networks: Comparison of Child-Focused Network Adequacy Standards between CHIP and Private Health Plans. GAO-16-219. Washington, D.C.: February 5, 2016. Children’s Health Insurance Program: Effects on Coverage and Access, and Considerations for Extending Funding. GAO-15-348. Washington, D.C.: February 27, 2015. Prenatal Drug Use and Newborn Health: Federal Efforts Need Better Planning and Coordination. GAO-15-203. Washington, D.C.: February 10, 2015. Children’s Health Insurance: Information on Coverage of Services, Costs to Consumers, and Access to Care in CHIP and Other Sources of Insurance. GAO-14-40. Washington, D.C.: November 21, 2013. Federal Autism Activities: Better Data and More Coordination Needed to Help Avoid the Potential for Unnecessary Duplication. GAO-14-16. Washington, D.C.: November 20, 2013. Dental Services: Information on Coverage, Payments, and Fee Variation. GAO-13-754. Washington, D.C.: September 6, 2013. Environmental Health: EPA Has Made Substantial Progress but Could Improve Processes for Considering Children’s Health. GAO-13-254. Washington, D.C.: August 12, 2013. Children’s Mental Health: Concerns Remain about Appropriate Services for Children in Medicaid and Foster Care. GAO-13-15. Washington, D.C.: December 10, 2012. Medicaid and CHIP: Considerations for Express Lane Eligibility. GAO-13-178R. Washington, D.C.: December 5, 2012. Medicaid and CHIP: Most Physicians Serve Covered Children but Have Difficulty Referring Them for Specialty Care. GAO-11-624. Washington, D.C.: June 30, 2011. Medicaid and CHIP: Reports for Monitoring Children’s Health Care Services Need Improvement. GAO-11-293R. Washington, D.C.: April 5, 2011. Page 56 GAO-18-41SP Child Well-Being Appendix IV: Related GAO Products Medicaid and CHIP: Given the Association between Parent and Child Insurance Status, New Expansions May Benefit Families. GAO-11-264. Washington, D.C.: February 4, 2011. Early Care and Education Early Learning and Child Care: Overview of Federal Investment and Agency Coordination. GAO-17-671T. Washington, D.C.: July 13, 2017. Indian Affairs: Actions Needed to Better Manage Indian School Construction Projects. GAO-17-447. Washington, D.C.: May 24, 2017. Indian Affairs: Further Actions Needed to Improve Oversight and Accountability for School Safety Inspections. GAO-17-421. Washington, D.C.: May 24, 2017. Youth with Autism: Federal Agencies Should Take Additional Action to Support Transition-Age Youth. GAO-17-352. Washington, D.C.: May 4, 2017. K-12 Education: Education Needs to Improve Oversight of Its 21st Century Program. GAO-17-400. Washington, D.C.: April 26, 2017. District of Columbia Charter Schools: Multi-Agency Plan Needed to Continue Progress Addressing High and Disproportionate Discipline Rates. GAO-17-165. Washington, D.C.: February 9, 2017. Youth with Autism: Roundtable Views of Services Needed During the Transition into Adulthood. GAO-17-109. Washington, D.C.: October 18, 2016. Child Care: Information on Integrating Early Care and Education Funding. GAO-16-775R. Washington, D.C.: September 14, 2016. School Choice: Private School Choice Programs are Growing and Can Complicate Providing Certain Federally Funded Services to Eligible Students. GAO-16-712. Washington, D.C.: August 11, 2016. K-12 Education: Education’s Experiences with Flexibility Waivers Could Inform Efforts to Assist States with New Requirements. GAO-16-650. Washington, D.C.: July 7, 2016. Page 57 GAO-18-41SP Child Well-Being Appendix IV: Related GAO Products K-12 Education: Better Use of Information Could Help Agencies Identify Disparities and Address Racial Discrimination. GAO-16-345. Washington, D.C.: April 21, 2016. Indian Affairs: Key Actions Needed to Ensure Safety and Health at Indian School Facilities. GAO-16-391T. Washington, D.C.: March 16, 2016. Indian Affairs: Key Actions Needed to Ensure Safety and Health at Indian School Facilities. GAO-16-313. Washington, D.C.: March 10, 2016. K-12 Education: Federal Funding for and Characteristics of Public Schools with Extended Learning Time. GAO-16-141. Washington, D.C.: November 30, 2015. K-12 Education: Internal Controls for Program Management and Oversight Can Help Ensure the Success of School Choice Programs. GAO-16-212T. Washington, D.C.: November 4, 2015. K-12 Education: Most Eighth Grade Students Are Not Proficient in Geography. GAO-16-7. Washington, D.C.: October 15, 2015. Indian Affairs: Further Actions on GAO Recommendations Needed to Address Systemic Management Challenges with Indian Education. GAO-15-597T. Washington, D.C.: May 13, 2015. Indian Affairs: Preliminary Results Show Continued Challenges to the Oversight and Support of Education Facilities. GAO-15-389T. Washington, D.C.: February 27, 2015. College-and-Career Readiness: States Have Made Progress in Implementing New Standards and Assessments, but Challenges Remain. GAO-15-104R. Washington, D.C.: December 12, 2014. Education of Homeless Students: Improved Program Oversight Needed. GAO-14-465. Washington, D.C.: July 31, 2014. Special Education: Additional Federal Actions Could Help Address Unique Challenges of Educating Children in Nursing Homes. GAO-14-585. Washington, D.C.: July 16, 2014. Early Learning and Child Care: Federal Funds Support Multiple Programs with Similar Goals. GAO-14-325T. Washington, D.C.: February 5, 2014. Page 58 GAO-18-41SP Child Well-Being Appendix IV: Related GAO Products Indian Affairs: Management Challenges Continue to Hinder Efforts to Improve Indian Education. GAO-13-342T. Washington, D.C.: February 27, 2013. Individuals with Disabilities Education Act: Standards Needed to Improve Identification of Racial and Ethnic Overrepresentation in Special Education. GAO-13-137. Washington, D.C.: February 27, 2013. School Bullying: Legal Protections for Vulnerable Youth Need to Be More Fully Assessed. GAO-12-785T. Washington, D.C.: June 8, 2012. Charter Schools: Additional Federal Attention Needed to Help Protect Access for Students with Disabilities. GAO-12-543. Washington, D.C.: June 7, 2012. School Improvement Grants: Education Should Take Additional Steps to Enhance Accountability for Schools and Contractors. GAO-12-373. Washington, D.C.: April 11, 2012. Hurricanes Katrina and Rita: Temporary Emergency Impact Aid Provided Education Support for Displaced Students. GAO-11-839. Washington, D.C.: September 7, 2011. School Improvement Grants: Early Implementation Under Way, but Reforms Affected by Short Time Frames. GAO-11-741. Washington, D.C.: July 25, 2011. Disadvantaged Students: School Districts Have Used Title I Funds Primarily to Support Instruction. GAO-11-595. Washington, D.C.: July 15, 2011. K-12 Education: Many Challenges Arise in Educating Students Who Change Schools Frequently. GAO-11-40. Washington, D.C.: November 18, 2010. Page 59 GAO-18-41SP Child Well-Being Appendix V: GAO Contact and Staff Appendix V: GAO Contact and Staff Acknowledgments Acknowledgments Kathryn A. Larin, (202) 512-7215 or larink@gao.gov GAO Contact In addition to the contact named above, Elizabeth Morrison (Assistant Staff Director), Avani Locke (Analyst-in-Charge), Linda Siegel, Sarah Acknowledgments Williamson, James Bennett, Carl Barden, Won “Danny” Lee, and Kay E. Brown made key contributions to this report. Also contributing to the report were Alicia Cackley, David Chrisinger, Sarah Cornetto, Sherri Doughty, Holly Dye, Rachel Frisk, Gretta Goodwin, Katherine Iritani, Susan Irving, Sara Kelly, Kristy Love, Janet Mascia, Sheila McCoy, Jean McSween, Diane Raynes, Cathy Roark, Paul Schmidt, Almeta Spencer, Scott Spicer, and Sarah Veale. (100765) Page 60 GAO-18-41SP Child Well-Being The Government Accountability Office, the audit, evaluation, and investigative GAO’s Mission arm of Congress, exists to support Congress in meeting its constitutional responsibilities and to help improve the performance and accountability of the federal government for the American people. 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