Household Income and Child Development in the First Three Years of Life (Phase 1) Household Income and Child Development in the First Years of Life (Phase 2)
Phase: NA
Conditions: Child Development, Brain Development, Household and Family Processes
Sponsor: University of California, Irvine

Research Strategy 
Household Income and Child Development in the First Three Years of Life 
(Baby's First Years) 
June 27, 2019 
NIH Rot HD087384 
[NOTE: The following is the Research Strategy submitted to NICHD on March 7, 2016 and approved and 
funded by NICHD. Some of the proposed measures in this document have been replaced by measures listed in 
the Analysis Plan Appendix Table I and Appendix Table II attached to this study registration. We have also 
edited some details in order to protect the anonymity of study participants.]
PROJECT SUMMARY 
Recent advances in developmental neuroscience suggest that experiences early in life have profound and enduring 
influences on the developing brain. Family economic resources shape the nature of many of these experiences, yet the 
extent to which they affect children's development is unknown. Our team of neuroscientists, economists and 
developmental psychologists proposes to fill important gaps in scientific knowledge about the role of economic 
resources in early development by evaluating the first randomized controlled trial to determine whether unconditional 
cash gift payments have a causal effect on the cognitive, socio-emotional and brain development of infants and 
toddlers in low-income U.S. families. Specifically, 1,000 mothers of infants with incomes below the federal pove1ty 
line from four diverse U.S. communities will receive monthly cash gift payments by debit card for the first 40 months 
of the child's life. Parents in the experimental group will receive $333 per month ($4,000 per year), whereas parents 
in the control group will receive a nominal monthly payment of $20. In order to understand the impacts of the added 
income on children's cognitive and behavioral development, we will assess treatment/control group differences at age 3 
(and, for a subset of measures, age 2) on measures of cognitive, language, memory, self-regulation and socio-emotional 
development. Brain circuitry may be sensitive to the effects of early experience even before early behavioral differences 
can be detected. In order to understand the impacts of added income on children's brain functioning at age 3, we will 
assess, during a lab visit, treatment/control group differences in measures of brain activity (electroencephalogram 
[EEG]). To understand how family economic behavior, parenting, and parent stress and well-being change in response 
to income enhancement, we will assess treatment/control differences in family expenditures, food insecurity, housing 
and neighborhood quality; family routines and time use; parent stress, mental health and cognition; parenting 
practices; and child care arrangements at child age 2 and, for a subset of these measures, child age 1. This study will 
thus provide the first definitive understanding of the extent to which income plays a causal role in determining early 
child cognitive, socio-emotional and brain development among low-income families.
SPECIFIC AIMS
Poor children often lag behind affluent children in language, memory, executive functioning and social­
emotional development, with corresponding differences in neural structure and function in brain regions that 
support these skills. • -4 As adults, poor children are likely to experience a range of unfavorable labor market and 
health outcomes.s Why this is the case is often debated, but not well understood. 6 Proponents of 
pove1ty­reduction policies point to the many ways in which economic hardship affects how parents provide for 
and interact with their children.7,8 Critics argue that what matters most is not the money itself, but other factors 
correlated with poverty such as being raised by a single mother or low parental education.9 
We propose to fill impo1tant gaps in scientific knowledge about the extent to which family pove1ty influences 
early-life development. We will conduct the first randomized controlled trial designed to evaluate the effects of 
unconditional income transfers on (1) the cognitive, socio-emotional and brain development of toddlers in 
low-income families; and (2) family economic behavior, parenting, and parent stress and well­being. The 
intervention, funded by non-federal sources, is a simple unconditional income transfer. Low-income families will 
be randomly assigned to a treatment group that receives cash payments of $333 per month-an amount roughly 
comparable to a variety of income assistance policies in the U.S. and shown to be associated with meaningful 
improvements for poor children in prior studies-or to a control condition that receives $20 per month. The 
payments will be made for the first 40 months of the child's life. The experiment will enable us to identify the 
causal effects of reliable and unconditional income payments on early child development in the U.S., informing 
not only our basic and applied scientific understanding of early development, but also shedding light on the role 
of anti-poverty policies in promoting the well-being of poor children.
Aim 1: To understand the impacts of cash payments on low-income children's cognitive and behavioral 
development by assessing treatment/control group differences at age 3 (and, for a subset of measures, age 2) in 
validated and reliable measures of cognitive, language, memory, self-regulation and socio-emotional 

functioning. 
Aim 2: To understand the impacts of cash payments on low-income children’s brain functioning at age 3 
by assessing treatment/control group differences using electroencephalographic-based measures of brain 
circuitry, including resting brain activity as well as the neural signatures of vocabulary development and 
memory formation.  
Based on prior research and theory, we hypothesize that cash supplements will affect young children’s 
development by changing the nature of their family contexts in two important ways: increasing investments 
and decreasing family stress. In the case of investments, additional income may enable poor parents to 
improve their children’s cognitive development by buying goods and services such as picture books and other 
sources of stimulation in the home; higher-quality non-parental child care; learning opportunities outside of 
the home; better housing and neighborhoods; and, by reducing or restructuring work hours, more parental 
time and interactions with children. Environmental enrichments such as these may improve children’s 
cognitive functioning, in particular language skills and IQ, via direct effects on brain development. 
Second, providing reliable cash payments may reduce low-income parents’ psychological distress, fatigue, 
stress and cognitive resource demands, all of which are adversely affected by constant financial juggling to 
make ends meet. With improved mental health and more cognitive resources (“bandwidth”), parents may have 
less conflict with each other (or other partners) and warmer and more responsive interactions with their 
children. They may also be better able to implement consistent and positive family routines – including regular 
medical and well-child check-ups. These improvements in family life and routines may enable both parents and 
young children to better regulate their physiological stress responses, thereby improving neural development 
in children’s brain areas that support executive functioning, memory, learning, socio-emotional development 
and health. Understanding the nature of these pathways constitutes our third aim: 
Aim 3: To understand the ways in which family and child developmental contexts are affected by 
unconditional cash supplements, we will assess treatment/control differences in family expenditures, food 
insecurity, housing and neighborhood quality, routines and time use, parent stress, parent-child interactions, 
parenting practices and child care arrangements at child age 2 and, for a subset of measures, at child age 1. 
Building basic scientific knowledge about the role that cash transfers, and resulting increases in income and 
reductions in poverty, play in the development of young children is crucial for improving the design of a range 
of anti-poverty policies and programs for families. 
 
RESEARCH STRATEGY 
Significance 
Recent advances in developmental neuroscience suggest that experiences early in life have profound and 
enduring influences on the developing brain, at a time when heightened plasticity is observed relative to later 
developmental periods.
10 Family economic resources shape the nature of many of these experiences, yet the 
extent to which they affect early-life development is not fully understood. Our team of neuroscientists, 
economists and developmental psychologists proposes to fill important gaps in scientific knowledge about the 
role of economic resources in early development by conducting the first U.S. randomized controlled trial to test 
whether unconditional cash gift payments have a causal effect on the cognitive, socio-emotional and brain 
development of infants and toddlers in low-income families. 
Social science studies provide evidence on the causal effects of family income on birth 
outcomes and older children, but not infants and toddlers. Many previous studies of income and 
poverty effects have used longitudinal data and natural variation in family income to assess how poverty relates 
to child development. These studies generally included demographic variables or other statistical adjustments 
to control for observable ways in which low-income families differed from more affluent families.
9,11,12 Not all 
studies draw the same conclusions, but the bulk of the evidence suggests that early childhood differences in 
family income at the low end of the income distribution are robust predictors of birth outcomes, children’s later 
achievement, educational attainment and even adult earnings.
5,13,14 In contrast, studies that either fail to 
differentiate family income by child age or focus on the broader income distribution typically found fewer and 
smaller income effects.
9,15 In all of this work, despite efforts to account for observable differences in family 
characteristics, the potential for bias from unobservable characteristics looms large. 
A smaller set of studies has sought to identify causal effects of low income by focusing on random-
assignment or quasi-experimental sources of variation in family income. The Negative Income Tax (NIT) 
experiments of the 1970s offered guaranteed incomes in the form of cash gift payments, with the generosity of 

payments declining as other sources of family income increased.6,16-18 The NIT evaluations were not designed to 
study infants and toddlers, but did gather limited data on children’s school outcomes. Results were mixed, with 
positive impacts on achievement in middle childhood and completed schooling in adolescence in some sites, 
but null impacts in others. 
More consistent quasi-experimental evidence of income effects comes from the welfare-to-work 
experiments of the 1990s, most of which increased employment and some of which also increased family 
income with earnings supplements. Although there were no comparable positive effects on achievement or high 
school completion among older children, in the case of low-income children making the transition into school, 
these studies indicated that income increases improved achievement and schooling outcomes, with a $4,000 
increase in annual income (in current dollars) for 2-3 years increasing school achievement by .18 standard 
deviation units.19,20 Our proposed experiment is powered to detect effects of this magnitude.  
Recent quasi-experiments have taken advantage of other sources of plausibly exogenous changes in family 
income, suggestive of what an unconditional cash transfer might provide. Studies exploiting variations in the 
timing of state- and province-specific expansions of U.S. and Canadian tax benefits for low-income families 
show that receipt of these types of cash gift payments contribute to higher test scores among elementary school 
children.
21,22 In other work, casino disbursements to Native American families have been linked to increased 
educational attainment for adolescents.23 Although the magnitude of income increases in these studies was 
only several thousand dollars, the increases account for a substantial share of a poor family’s income—often 
20% or higher—and the effects on children’s outcomes were large enough to be meaningful.  
Related evidence on income effects comes from recent evaluations of programs providing conditional or 
unconditional cash transfer payments to low-income families. First tested in developing countries as a way to 
incentivize children’s continued schooling and medical care, conditional cash transfers (CCTs) often produced 
significant improvements in children’s development, education and health. This is attributed to the structure of 
CCTs, which provide incentive payments that directly offset the specific and large opportunity cost of the 
desired behavior.24 In the U.S., the evaluation of Opportunity New York City (ONYC), a CCT program targeting 
reduced family poverty and economic hardship, showed no impacts on children’s school test scores after two 
years of participation.25,26 Possible explanations for the null effects include the complexity of the payment 
schedule, the diversity and complexity of behaviors being targeted, implementation difficulties, the small 
amount of cash support relative to the high cost of living in New York, and the fact that children were older 
than those enrolled in many other income studies. Unconditional cash transfers (UCTs), sometimes bundled 
with other benefits, show some promise in improving economic well-being among participants in the 
developing world, but remain untested in the U.S. context.27,28  
Although the findings from these social science studies are informative, none of the prior studies focused 
on infancy and toddlerhood, the time when the developing brain is most malleable to environmental context. 
Their focus on older children arose from logistical constraints, including the difficulty and cost of collecting 
valid developmental measures from young children, the exemption of mothers with very young children from 
welfare-to-work experiments, and the challenge of conditioning cash transfers on behavior relevant to infants 
and toddlers. Second, many U.S. policy studies were based on income increases that were conditioned on or 
bundled with employment, which complicated efforts to isolate causal impacts of the income transfers per se.  
New neuroscience studies find family income correlates with brain function and structure, 
but lack causal evidence. An important advance in neuroscience has been the study of how early 
environments, especially adverse environments, shape brain development.29 A subset of these studies has 
focused on family socioeconomic status (SES) generally or on income specifically as a key dimension of early 
contexts.
1-3 In contrast to the social science literature, these studies focus on specific cognitive skills and, 
increasingly, on direct measures of brain development. This innovation is critical because differences in neural 
circuitry are often evident well before general cognitive or behavioral differences can be detected,10,30 and thus 
serve as an early indicator of the development of cognitive disparities. Moreover, neuroscience provides an 
explanatory framework for the physiological mechanisms that lead to lower cognitive skills and other observed 
behavioral differences. Distinct brain circuits support discrete cognitive skills, and differentiating between 
these underlying neural systems may point to different causal pathways and approaches for intervention.
2,31-33 
Neuroscience studies have documented SES differences in language, memory, executive function and socio-
emotional processing.2,31,33-35 For example, Noble and colleagues found that, by the start of school, 
socioeconomic factors were associated with language skills, memory and executive functions at substantial 
magnitude (effect sizes of .25-.50 standard deviations).
31 Similar socioeconomic disparities in neurocognitive 
skills have been reported from toddlerhood through adolescence.
32,34,36 SES-based differences have also been 
found in the structure and function of brain regions that support these skills in studies of older children and 

Child 
outcomes
Timing of measurement:
Income 
supplement
ation
Investment 
pathway
Stress 
pathway
Continuous 
birth to 
age 3
Mostly
 ages 1 and 
2; some 
continuous 
Mostly
 age 3; 
some age 2; 
some tracked 
beyond  age 3
adolescents using MRI techniques.
1,37-45 For example, four independent labs have reported that family income 
is associated with the volume of the child’s hippocampus, a part of the brain that is related to memory and 
learning,
39,41,45,46 One large study recently reported associations between family income and the size of the 
brain’s surface, particularly in regions supporting children’s language and executive functioning; this 
association was strongest among the most disadvantaged families.1 
Several small-scale correlational studies have reported that income is related to differences in early 
childhood brain function as early as 6 months of age.47,48,49 Studies by members of our team and others have 
shown that these early measures of brain function are correlated with better cognitive
50 and verbal51,52 abilities 
in later childhood and adolescence. Similarly, poverty and economic deprivation have been correlated with 
neural patterns48,49 that have been associated with later behavioral and attention problems.
53 Importantly, 
reducing adversity can partially normalize these patterns.
54  
Neuroscience studies suggest that the early experience of poverty may shape children’s brain development, 
and that such mechanisms may underlie observed differences in subsequent cognitive skills, behavior, school 
completion and achievement. However, despite the specificity and rigor of brain measurement, these 
descriptive studies of small samples support neither causal inference nor population generalizability.  
Generating additional evidence about the pathways by which income affects the 
development of low-income children will advance scientific knowledge. A large social science 
literature has documented that poverty is associated with lower quality caregiving environments,
55-60 but these 
studies are largely correlational, precluding strong 
conclusions about the causal nature of the associations. Our 
study will estimate causal impacts of increased income, as 
generated by unconditional cash supplements, on key 
dimensions of family life, which we conceptualize in two 
main pathways. First, economic models view families with 
greater income as better able to purchase or produce 
important inputs into their young children’s development. 
This investment pathway results in children 
experiencing more materially enriching early environments. 
Second, psychologists and sociologists point to the ways in 
which economic disadvantage impairs children’s 
development through a stress pathway. This pathway 
includes income effects on the quality of family 
relationships
59,61,62 as well as on biological indices of chronic 
stress.
63-66 These pathways have shown distinct associations with developmental outcomes, with generally 
stronger impacts of investment on early cognitive skills and stronger impacts of the stress constructs on early 
socio-emotional skills.  
Investment Pathway. Low-income parents face steep challenges in meeting basic financial needs and 
ensuring that resources are available so that they can adapt to fluctuations in income and expenses.67,68 Many 
poor families are not only cash-constrained, but they also have few savings and lack access to low-cost sources 
of credit.69-74 As a result, when faced with income shortfalls, they are often forced to cut back on expenditures, 
even for essential goods such as food and housing, and to pay high interest rates on small but accessible loans.75 
A predictable monthly cash income supplement in the first 40 months of life may support children’s cognitive 
development by enabling poor parents to meet basic needs and further invest in goods and services for their 
families, such as cognitively stimulating items in the home; higher quality non-parental child care; learning 
opportunities outside of the home; and, by reducing or restructuring work hours, more parental time and 
interactions with their child.
76-78 Early maternal employment has null to negative effects on cognitive 
development, suggesting that reductions in employment induced by our payments may be beneficial for some 
children. Higher monthly income may also contribute to better housing or moves to better neighborhoods. 
Evidence from studies of poverty reduction and income supports has shown that these programs reduce 
material hardship and improve aspects of children’s learning environments as well as their participation in 
enriching child care and activities.79,80 Studies of near-cash benefits and patterns of family expenditures 
provide related empirical support to these pathways.58,81-84 Moreover, analysis of observational data finds that 
cognitive stimulation and learning resources partially explain the effects of poverty on children’s 
achievement.55,57 Finally, evaluations of the Negative Income Tax, casino disbursements and a Kenyan UCT did 
not find offsetting or harmful behavior, such as alcohol or cigarette expenditure or consumption.23,85,86 All of 
these family processes will be measured in our study, with questionnaires and videotaped parent-child 
interactions. 

Investments and enrichments may improve children's cognitive functioning, in pa1ticular language skills, 
IQ and other pre-academic skills, through direct effects on brain development.39,87 For example, children's 
experience of cognitively stimulating activities is related to the development of language-supporting brain 
regions, as measured by ERP.88-97 Direct studies of associations between family income and neural 
development are scarce, and are largely limited to school-aged children and adolescents.39,98,99 
Stress Pathway. Income may also affect other aspects of family functioning among low-income families. 
Seminal work in this area focused on parents as the primary conduits of stress in households - that is, 
economic hardship increases parental psychological distress and decreases emotional well-being, which in turn 
creates conflict and withdrawal in family relationships and results in parent-child interactions that are more 
negative and harsh as well as less nurturing and suppo1tive.60-62 Recent work has broadened the focus on 
parents' psychological well-being to include other dimensions of children's experiences, and has recognized 
that many aspects of poor children's environments challenge their adaptive systems, including instability in 
family structure, chaotic routines and violence. The co-occurrence of these environmental threats accumulates 
in children's lives and creates emotional and physiological stress, including alterations in cortisol.59,100-102 
Reducing parents' psychological strain and the stress that children themselves experience may improve 
children's cognitive functioning, in pa1ticular memory, executive functioning and socioemotional skills, 
through direct effects on brain development. Reductions in family stress are likely to benefit the regulation of 
children's stress physiology, 103-105 thereby improving neural development in the areas of the brain that are
particularly sensitive to the effects of chronic stress. Among infants, lower cortisol levels during a learning task 
are linked with better learning and memory skills,1°6 suggesting that early-life stress may impede memory 
development in early childhood. Similarly, early adversity has been associated with differences in the neural 
responses underlying memory formation.1°7 However, direct studies of associations between family income and 
the neural basis of learning and memory development have been limited largely to older children and 
adolescents,39A1,44-46 and do not yet support causal inference. 
The hypothesized investment and stress pathways differ in their developmental mechanisms, but are 
overlapping and reinforcing. For example, both increased economic resources and improved mental health and 
family routines may result in higher quality child care, more cognitively enriching out-of-home activities, and 
more visits for preventive medical or dental care. Moreover, downstream effects may be bidirectional; for 
example, more verbal children may trigger more speech and book reading from their parents. In addition, the 
particular pathways might be different for different families but still contribute to similar magnitudes of 
income effects on children's developmental outcomes.108 
The investment and stress pathways are complemented by behavioral science studies of cognitive resources 
and decision making. Enhanced family income may create more enriching and less stressful family 
environments by reducing the cognitive load that parents face.109-112 Studies show that conditions of scarcity 
place demands on limited cognitive resources, directing attention to some problems at the expense of 
others.110,
111 Thus, low income may interfere with parents' efforts to take care of their children's basic needs by 
rendering them less able to plan for and engage in activities that may enrich their children's lives. Ours will be 
the first RCT study to test impacts of income supplementation on maternal "bandwidth." 
Informing policy debates on the consequences and benefits of conditional and 
unconditional income support policies. Beyond its core contributions to science, this study will provide 
important evidence about the likely effects of tax and transfer policies on young children in the U.S. The benefit 
levels and coverage of such programs (e.g., earned income and child tax credits, food assistance) are debated 
fiercely in today's state and federal budget battles.113 Absent from these debates is causal U.S. evidence on the 
consequences of proposed changes to these programs for the development of very young children in low­
income families. The $333 monthly cash gift payments comprising the intervention in this study are consistent 
with the size of income increments associated with changes in children's cognitive and socio-emotional 
development, and are well within the financial range of benefits of existing programs that are active in ongoing 
debates. 
Innovation 
Our proposed study fills large gaps in the social and behavioral sciences and in developmental 
neuroscience. It will be the first large-scale U.S. experiment involving unconditional cash transfers 
to poor families with infants. As such, it will improve on prior experimental and quasi-experimental 
studies of child wellbeing that increased family income with in-kind supports or by conditioning income 
increases on employment or other behaviors. Furthermore, it complements studies offering similar types of 
unconditional cash to the very poor in low- and middle-income countries. 27 Our study tests the idea that 
regular, reliable cash gift income transfers improve child development and improve family environments 

among poor families. Second, by specifically transferring income to families during their children’s 
earliest developmental years, this study will provide important evidence on income effects during a period 
when children’s development is particularly sensitive to family economic circumstances, and when children’s 
brains are most plastic and responsive. Third, we are among the first to employ neuroscience methods for 
measuring brain function in the context of a large social science experiment, which will provide 
the strongest causal evidence to date on the neural mediators linking income to child outcomes. These neural 
mechanisms may serve as an early indicator of income’s effects, and our findings may shed light on the 
mechanisms responsible for behavioral change. Fourth, ours will be the single largest longitudinal 
study of early childhood development that combines socioeconomic, parental well-being, and 
family functioning social science measures and methods with biological stress and 
neuroscience-based assessments of children’s development. Our comprehensive data collection and 
measurement plan – at baseline and at child ages 1, 2, and 3 – will allow us to assess a host of cognitive and 
socio-emotional skills that play a major role in the cognitive neuroscience literature, including language, 
memory, executive functions and socio-emotional development, as well as a broad range of pathways by which 
increased income is hypothesized to impact children’s developmental outcomes. Despite the huge potential 
advantages of cross-fertilization, neuroscience research on SES and cognitive development and related 
research in the social and behavioral sciences have moved forward quite independently of one another. The 
synergistic combination that we have developed in our collaborative planning for this study over the past 3.5 
years is unprecedented: random assignment, rigorous sampling and survey methods, state-of-the-art 
measurement of parenting and other family processes, coupled with laboratory methods from neuroscience 
including centralized analysis of electrophysiological and stress physiology data. Finally, this study will 
leverage private philanthropic funding of $5.81 million in cash supplements to undertake the 
intervention, using governmental funding to evaluate the impacts of this increased income.  
Approach 
This project will be led by four Principal Investigators: Greg Duncan, PhD in economics; Kimberly Noble, 
MD, PhD in neuroscience; Katherine Magnuson, PhD in human development and social policy; and economist 
Lisa Gennetian, PhD. Psychologist Hirokazu Yoshikawa, PhD and neuroscientist Nathan Fox, PhD form the 
rest of our core team of project investigators. Our collective experience includes direction of large longitudinal 
data collection projects (e.g., Panel Study of Income Dynamics), design of and participation in birth cohort 
studies using hospital recruitment, and experimental studies (e.g., Bucharest Early Intervention Project; 
Moving to Opportunity housing mobility experiment; welfare-to-work experiments conducted by MDRC; Un 
Buen Comienzo preschool experiment in Chile). Several of us have written widely-cited studies of the 
neuroscience (Noble) and social science linkages between poverty and child development (Duncan and 
Magnuson). Each of us has collaborated closely with one or more of the other members of the team on major 
federally-funded research projects.  
We have partnered with neuroscientist co-Is in each proposed study site to oversee the collection of 
neuroscientific data collection at age 3: Michael Georgieff, MD (pediatrics) at the University of Minnesota, an 
expert in infant brain development and neurocognitive function; Connie Lamm, PhD in Psychology at the 
University of New Orleans, an expert in the electrophysiological correlates of self-regulation; Dennis Molfese, 
PhD, Timothy Nelson, PhD and Jennifer Nelson, PhD, all in Psychology at the University of Nebraska and 
experts in using brain recording techniques to study brain development and cognition; and William Fifer, PhD 
in Psychology at Columbia, an expert on infant experience, electrophysiology, and learning, and who will 
oversee the electrophysiological data collection in New York as well as the pooled data processing and analysis 
of all EEG/ERP data collected across the sites.  
Charles Nelson, PhD, and Charles Zeanah, MD will serve as consultants to the project, providing their 
extensive expertise in measuring brain function and stress physiology in randomized experiments involving 
children facing extreme early adversity. A multidisciplinary advisory board consisting of neuroscientists and 
social scientists will provide feedback over the duration of the project: W. Thomas Boyce, a pediatrician with 
expertise in neurobiological and psychosocial processes; Flavio Cunha, an economist who studies parenting 
strategies in low-income families; Kathryn Edin, a mixed-method sociologist whose studies how low-income 
families "make ends meet"; Bridget Goosby, a health demographer who studies how stratification and 
discrimination affect biological processes among racial and ethnic minority families; Bruce McEwen, a 
neuroscientist with expertise on the effects of stress on neuroplasticity; Eldar Shafir, a psychologist with 
expertise on cognitive decision making in the context of poverty; and Michael Lopez, a child psychologist who 
has worked closely with policymakers on early childhood interventions for Hispanic children. 
Pilot Study. With separate funding, in June 2014 we launched an IRB-approved pilot study of 30 poor 

mothers of newborns from New York Presbyterian Hospital/Columbia University Medical Center to assess 
baseline procedures, implementation of the debit card and cash transfer, and pilot data collection to inform the 
development of final survey data instruments and home assessments (see Appendix 1). Greenphire 
(greenphire.com/home) was selected from several companies to administer the payments and provide toll-free 
customer service. Their pre-paid debit card does not require a bank account, and can be used to make 
purchases directly at stores ("point-of-service") or to withdraw cash at ATMs or banks. Mothers consented to 
have Greenphire share information about their debit card transactions with the research team. Cell-phone texts 
ale1ted each mother about monthly payments. 
Thirty mothers pa1ticipated in the baseline survey, indicated a willingness to be contacted for future data 
collection, and agreed to pa1ticipate in randomization to one of two cash receipt conditions. The pilot sample 
was largely African American (67%) and Hispanic (70%, mostly Dominican; 37% completed surveys in 
Spanish). Average maternal age was 25.9; average repo1ted income was $22,311; and average household size 
was 4.6. Half of the infants were first-born. 
After completing a baseline interview, 15 of the 30 mothers were randomly assigned to receive $100/month 
for 12 months (smaller payments than in the proposed study), and 15 were assigned to receive $20/month for 
12 months. Twenty-nine of the 30 mothers consented to our tracking of administrative records data and debit 
card transactions. Baseline differences in background characteristics favored neither group, suggesting 
successful randomization. Debit cards were given out immediately following the baseline interview; all mothers 
used their cards within 6 weeks and regularly thereafter. Very few reported substantial issues with the card, 
such as a loss or theft, fraudulent charges, or needing help resetting PINS. At 12 months, 27 mothers completed 
a survey interview closely resembling our proposed age-2 home visit, with an in-home assessment of family 
expenditures, routines and time use, parent stress and parenting practices, and child care arrangements. (In 
the pilot, we did not contact the 3 mothers who moved out of state, though this effo1t would be made for the 
proposed larger study.) Despite the small sample size (13 treatment and 14 control mothers), differences of 
over .5 standard deviations were found favoring the treatment group for reduced household chaos as well as 
increased mother-child learning activities and child-care expenditures; the latter was statistically significant 
(p<.05). The pilot study suggests that study implementation, methods of income transfer and research strategy 
are feasible with low-income mothers with infants, in ways that can support the research at scale. 
Research Design. The proposed study will enroll a total of 1,000 mothers of newborn infants with 
household cash incomes in the prior calendar year below the official poverty line for households of their size 
(including the infant as a household member). Enrollment will be evenly distributed across four sites: New 
York City; the greater New Orleans metropolitan area; the greater Omaha metropolitan area; and the Twin 
Cities. A total of 12 hospitals will participate, but we do not list them in order to preserve participant 
confidentiality. 
The four sites were selected because they are diverse in terms of racial and ethnic composition of low­
income residents, cost of living, urbanicity, and the generosity of state safety net programs such as Temporary 
Assistance to Needy Families (TANF) and state Earned Income Tax Credits (EITC); see Appendix 2. 
Recruitment (and our three subsequent annual data collections) will be spread evenly over the course of 12 
months to avoid possible impacts of seasonal variation and to keep interviewer workload manageable. The 
Survey Research Center (SRC) at the University of Michigan will enroll pa1ticipants and conduct baseline and 
age 1 survey interviews, survey interviews and home observation assessments at age 2, and survey interviews in 
the lab at age 3. SRC is especially skilled in fielding national studies that replicate protocols across multiple 
sites with high fidelity and provide data for the ongoing monitoring of the quality of recruitment effo1ts and 
data integrity. Extra quality assurance of these elements, as well as all age-3 cognitive and EEG data collection, 
will be conducted by our research team. The research team will also collect administrative data to obtain 
ongoing measurement of earned income and public benefits, possibly including health and Medicaid records 
and child protective services involvement. Conditional on early-wave findings, we will seek additional funding 
for follow-up assessments and analyses beyond the children's third birthdays, including obtaining additional 
administrative data such as school records for the target children and their siblings. 
Intervention. The intervention in this project is a simple income manipulation in the form of cash gift 
payments to families, funded by philanthropy. Mothers in the treatment group will receive monthly cash gift 
payments of $333 ($4,000 per year) for the first 40 months of the child's life, paid on the day of the month of 
the child's bi1thday by automatic loading on an electronic debit card. To put the magnitude of the payments in 
context, the proposed annual income supplement of $4,000 would increase income in the average poor family 
in our pilot study by about 20%. Monthly text messages will announce the payment to recipients. We propose 
to pay families for 40 months to ensure that the age-3 lab-based data collection occurs well before the end of 
our cash gift payments. In order to eliminate any payment-mode effect, the control group will receive a 

nominal payment -- $20 per month, delivered in the same way as for the experimental group. Debit cards are a 
superior mode of cash transfer for practical reasons (e.g., few low-income individuals have bank accounts) as 
well as for conceptual reasons: We wanted to preserve the unconditional cash transfer nature of the transaction 
and enable point-of-sale or ATM cash transactions. As in the pilot study, Greenphire will administer the debit 
cards to the mothers. Our pilot study experience suggests that all mothers will use their debit cards regardless 
of experimental condition, thus leading us to expect that take up will be near-universal. 
We have secured the appropriate exemptions or approvals in all of our sites to ensure that the mothers will 
not lose eligibility for virtually all public benefits as a result of our cash gift transfer. Specifically, our cash gift 
payments will be exempted from countable income in the determination of benefits from relevant programs, 
including TANF, SNAP, WIC, Medicaid, Housing Choice Vouchers, child care subsidies, and Head Start. 
Enrollment Procedures. Mothers will be recruited in maternity wards of participating hospitals shortly 
after giving birth (see Appendix 1; 98.6% of all births in the US in 2012 occurred in hospitals, with a higher 
percentage among births to low-income, Black and Hispanic women).114 Eligibility criteria include: (1) mother 
18 years or older; (2) household income below the federal pove1ty threshold in the calendar year prior to the 
interview, counting the newborn; (3) infant admitted to the newborn nursery and not requiring admittance to 
the intensive care unit; (4) residence in the state of recruitment; (5) mother not "highly likely" to move to a 
different state or country in the next 12 months; (6) infant to be discharged in the custody of the mother; and 
(7) English or Spanish speaking (necessary for the child outcome measures). Census data for our hospitals'
catchment areas suggest our sample will be roughly 35% African American, 45% White (including Hispanics),
7% Asian, 14% other; 20% are expected to also identify as being Latino. Births will be stratified by parity and
differentially sampled if necessary to ensure an adequate
representation (35% or more) of first births and a small number
(10% or fewer) of births that were preceded by 3 or more births to
the same mother. In 2013 national fertility data, 40% of all bi1ths
(and 37% of non-Hispanic Black and 33% of Hispanic births) were 
first births, while 12.% of all births (and 16%of both non-Hispanic 
Black and Hispanic births) were fourth or higher parity. 
Sample recruitment strategies and exclusion criteria are 
designed to balance external validity of the sample with respect to 
all poor families with newborns, optimize the target population for 
whom this intervention might be most powerful, and minimize 
difficulty and expense of recruitment and follow-up. We include all 
families living in poverty for several reasons. First, prior quasi­
Month 
1-6 
7-18 
10-.'W 
.11-42 
43-54
19 -54 
4t;-t;4
55-60
S7-60 
Primaru Activitu
Proiect planning
Hospital-based recruitment and
baseline interviews
Age-1 telephone interviews
Age-2 in home interviews
Age-3 lab assessments 
Gather and process data from
administrative records 
Im pact analysis of family process 
Impact analysis of child 
outcomes 
Prepare data for release 
experimental studies have found positive income effects for all poor families, regardless of depth of poverty. 
Second, although our payments represent a larger proportional transfer to families in deep poverty, 
conceptually, it is not clear that the poorest families are uniquely able to use the money to improve child 
outcomes. In keeping with our goal of informing policy debates on the consequences and benefits of income 
support policies, use of the poverty-line threshold matches best with the population commonly targeted by U.S. 
means-tested social policies. 
Sampling mothers from a hospital rather than a community-based organization or social service agency 
increases the likelihood that families are representative of low-income communities served by the hospital. 
There is no comparable cost-effective gateway to recruit prenatally and achieve similar generalizability. 
Because first-time parent(s) tend to be earlier in their earnings profile, the economic conditions of first-birth 
children are, on average, worse than for higher-parity children. Further, the proportion of money available to 
the target child will be larger for small families, motivating a special interest in first bi1ths. On the other hand, 
the generally younger mothers of first births may be less effective in managing their income supplements than 
the older mothers of higher-parity bi1ths. These competing considerations lead us to opt for representation of 
children of all parities, but to stratify our sample by parity as described above. 
At the time of hospital-based screening and recruitment, SRC will conduct a baseline survey and obtain 
informed consent for study pa1ticipation (including consent for survey, observational, physiological, and 
administrative data). We plan to identify 1,200 eligible mothers, with 1,000 pa1ticipants expected to take up 
the lottery offer. Mothers will be told that study pa1ticipation involves three subsequent data collection points 
(although they will be free to withdraw from the study at any time without penalty). At the child's first birthday, 
a phone interview will be conducted with the child's caregiver, who will be the mother in most cases. At the 
child's second birthday, an in-home interview and observational assessment will be conducted. At the child's 
third birthday, caregivers and children will participate in a laboratory assessment. Following standard research 
procedures, all participating families will receive a cash incentive ($50) for participating in each of the baseline, 

age 1 and age 2 interviews, and a larger incentive ($200, plus transportation costs) for the age 3 laboratory 
assessments. 
To address ethical concerns about large gift payments coercing mothers to pa1ticipate in research, mothers 
will consent to participate in the research study, complete the baseline survey, and be compensated for 
completing this survey prior to learning about the possibility of monthly cash gift payments. Following 
questionnaire completion, the mother will be offered the opportunity to enter a lottery, in which 40% will be 
randomly assigned to receive a $333 monthly cash gift payment and 60% will receive a $20 monthly cash gift 
payment. Mothers will not be told of the amounts of the two payments prior to providing consent. Mother who 
agree to participate in the lottery will then learn whether they will receive $333 or $20 months cash gifts, be 
handed their debit card, and be given instructions on its use with the oppo1tunity to ask any questions. These 
baseline procedures worked well in our pilot study. 
To avoid coercion, we will explain to the mother that her pa1ticipation in the lottery is completely 
independent of her subsequent research pa1ticipation. That is, cash gift payments will be not conditioned on 
subsequent participation in the research. Although a small number of women may then choose to take the cash 
gift payments and decline to participate in the future research, we think this is quite unlikely as (1) participants 
will have already indicated a willingness to pa1ticipate in future data collection effo1ts, (2) SRC has an 
outstanding track record of recruitment and retention and (3) the research activities will be separately 
compensated. None of the 30 pilot study mothers has refused our interview requests. 
Child Outcome Measures. We will collect a host of age-appropriate measures of children's cognitive, 
behavioral and brain functioning (see also Appendix 4 for details). A subset of these measures are proposed for 
preregistration in clinicaltrials.gov. 
Child language and cognitive measures at age 3 (lab visit). We will administer tasks to assess language, 
memory, and self-regulation, all of which are normed from age 3 through adulthood and validated for both 
low-SES children and children whose primary language is English or Spanish. This will enable us to continue to 
follow up children on the very same tasks at older ages through future funding proposals. We will assess IQ 
using the Wechsler Preschool and Primary Scale of Intelligence-IV (WPPSI). 
Child social and emotional measures at age 3 (lab visit). We will employ the Preschool Self-Regulation 
Assessment, an experimenter-report measure of the child's regulation during the testing session. Additionally, 
the BITSEA, a standardized questionnaire measure that assesses social and emotional competence in young 
children, will be administered to mothers, providing subscales of internalizing and externalizing broadband 
problems validated with low-income populations.117 
Brain activity at age 3 (lab visit). Nearly all studies of brain development in early childhood rely on 
electrophysiological techniques such as electroencephalography (EEG).118 These techniques measure the 
electrical activity of the human brain ( or "brainwaves") by placing electrodes on the scalp and amplifying the 
signal. Changes in voltage are then plotted over a period of time. While EEG is measured while the child is "at 
rest," ERP assesses the child's neural response to a particular set of stimuli, such as words or pictures, to better 
understand how children's brains are functioning during particular cognitive tasks. Both techniques measure 
brain function with precise temporal resolution (on the order of milliseconds) and modest spatial resolution. 
Most importantly, these approaches allow the young child to sit comfortably next to a caretaker or on the 
caretaker's lap, thereby facilitating the collection of high-quality data with a population that may not easily sit 
still. Although MRI provides higher spatial resolution, pa1ticipants must lie perfectly still in a dark and noisy 
tube, and while very young infants may fall asleep in the scanner, many older infants and toddlers will not. 
Thus, while studies have on occasion been successful in obtaining MRis in very young children,42,119,120 most 
large-scale studies of structural brain development do not take this approach because of the threat of 
significant amounts of missing data.119,12° Functional MRI (fMRI) - obtained while a child is engaged in a 
cognitive task, thereby providing information on brain function as opposed to structure - poses even more 
logistical challenges for very young children, and is rarely if ever attempted with infants and toddlers. 
The brain signals recorded with resting EEG are commonly quantified using power, an index of co1tical 
activation reflecting synchronous currents within a local neuronal population.121 This signal is decomposed 
into oscillations that occur in different frequency bands. Researchers can examine how the power of the signal 
varies by frequency band across the scalp, representing differences in activity in different regions of the brain. 
To avoid undue pa1ticipant burden, we focus on the effects of income supplementation on the neural 
development of language and learning/memory, two neurocognitive systems that show marked individual 
differences and malleability to early environmental context, and which we expect will be differentially affected 
by our hypothesized investment and stress pathways, respectively. We will collect all electrophysiological data 

on 128-lead, high-density Electrical Geodesics Inc. (EGI) systems using identical procedures across the four 
sites, as have been described in numerous experiments in the co-investigators’ labs.
122-133 Each lab has prior 
experience collecting these measures with low-income families and toddlers. All raw EEG and ERP data will be 
transmitted via secure electronic transfer to Co-I Fifer’s lab at Columbia for central processing and analysis. 
Data from resting EEG will include spectral power and coherence. Several small-scale correlational studies 
have reported that income is related to differences in early childhood resting EEG power as early as 6 months 
of age.47,48,49 Specifically, family income has been correlated with power in the frontal region in the gamma 
frequency band.
47 We therefore hypothesize that children in the intervention group will show greater frontal 
gamma power relative to children in the control group, a pattern which has been associated with the 
development of better cognitive50 and verbal51,52 abilities. Poverty and economic deprivation have also been 
correlated with an excess of theta EEG power and a deficit in alpha power,
48,49 which in turn have been 
correlated with later behavioral and attention problems. 
48,49,53 We therefore hypothesize that the intervention 
group will show reduced theta power and greater alpha power than children in the control group.  
We will also obtain ERP measures of children’s language88,134 processing. To assess language development, 
we will measure children’s neural response to known vs. unknown words (as categorized by the mother). Audio 
presentation of the words results in a series of positive and negative deflections of voltages on the scalp. By 
convention, ERP signals are typically named according to whether the amplitudes of these deflections are 
positive (“P”) or negative (“N”), and the number of milliseconds following the stimulus at which they occur. In 
toddlers, the amplitudes of the N200, N350 and N600-900 ERP components are larger to known words 
relative to unknown words. This contrast between known and unknown words becomes progressively more 
lateralized to the left side of the brain with age.
134 It is hypothesized that children in the intervention group will 
show greater left-lateralization of these components for known words relative to children in the control group, 
indicating a more advanced neural signature of vocabulary development.  
Child cognitive measures at age 2 (home visit). Although our primary cognitive, social-emotional and brain 
outcome measures will be administered at age 3, we will obtain brief measures of children’s cognitive 
development at the age 2 home visit (noting that many of the age 3 measures are not appropriate for children 
this young). Specifically, we will administer the Mullen Scale of Infant Development. In addition, we will 
videotape a 15-minute free play and clean-up mother-child interaction using a consistent set of small toys and 
code it for child language output (mean length of utterance, types and tokens) using approaches our team has 
experience using with diverse low-income families.
139  
Family Process Measures. We will obtain multiple measures of family processes that are hypothesized 
to explain the poverty-brain connections and represent our secondary outcomes of interest (see also 
Appendices 5 and 6). Data will be obtained through surveys and interviewer observations. All survey measures 
described below have been validated in prior large-scale studies of low-income families conducted by our team. 
A subset of these measures are proposed for preregistration in clinicaltrials.gov. 
Economic resources and investment at ages 1, 2, and 3. Survey measures of the nature and use of economic 
resources will include families’ total income and earnings, debt and savings as well as indicators of economic 
hardship, food insufficiency, and household expenditures. Our measure of total income will enable us to 
measure the net family income increased by the cash supplements, while details on income flow to and from 
family members living outside the household, combined with household rosters, will enable us to assess how 
much of the increased income is shared across extended families. We also will request administrative data from 
state and county programs to measure income using Unemployment Insurance (UI)-based quarterly earnings 
and state records of TANF, SSI, CCDBG child care subsidies, and SNAP (food stamp) payments. These 
administrative data will provide us with a second source of information on income and benefit use. Given 
potential family mobility across states and counties, within reason we will attempt to obtain data from as many 
state and county programs as possible. In the Moving to Opportunity (MTO) study, we were able to collect data 
for over 90% of a comparable low-income sample.  
Information about the quality and characteristics of housing and residential histories will be collected by 
observation (at age 2), and from parent surveys and GPS-address data matching, which will enable us to test 
whether income supplements are used to pay for moves to better housing units and/or neighborhoods. 
Information about parental employment and non-parental child care, including the type, amount and cost of 
care, will be collected from parent surveys. Details on hours worked, scheduling of those hours, total number of 
hours, and predictability of work schedules will enable us to test for differences in the timing of the mother’s 
return to part- or full-time work following the baby’s birth and for differences in the longer-run division of 
maternal work hours between none, part time, full time and more than full time (e.g., from overtime or second 
jobs). Data on type and cost of child care will enable us to assess whether income supplements are used to 

access center-based and/or more expensive care. Surveys also will gather information about cognitively 
stimulating activities, learning materials, and parental time spent with children. We will ask about child 
enrichment expenditures as well as spending that might crowd out additional spending on children in negative 
ways, such as on cigarettes and alcohol. Finally, the age 2 videotaped mother-child interaction will be coded for 
maternal linguistic input, including number of words spoken to the child, mean length of utterance, and 
types/tokens.
139 
Maternal and child stress physiology at age 2. To obtain direct physiologic indices of stress dysregulation, 
hair cortisol (capturing cumulative stress) and salivary cortisol (capturing stress reactivity) will be measured in 
children and mothers at the age 2 home visit. Because hair follicles accumulate cortisol continuously, hair 
cortisol acts as a biomarker for chronic stress of the type experienced by low-income populations.
65,140-142 
Additionally, hair assays provide a very stable measure of cortisol that can be obtained noninvasively in a single 
sample, free of many of the methodological challenges associated with collecting diurnal salivary cortisol, 
including susceptibility to minor perturbations due to food intake, time of acquisition, or acute stressors.
143,144 
Despite the relative recency of this technological advance, low SES has been associated with higher hair cortisol 
in both adulthood
143 and early childhood,145,146 and preliminary data suggest that associations with income are 
strongest among low-income families.
147 To assess stress reactivity, we will collect salivary cortisol at baseline, 
prior to, and following presentation of a mildly stressful stimulus (a scary mask).This technique has been 
successfully implemented in disadvantaged families with young children.
103,148-151 We will assess treatment 
group differences in baseline cortisol, reactivity and recovery, with attention to heightened and/or blunted 
reactivity, both of which are considered signs of dysregulation. Finally, we will videotape these interactions for 
later coding of treatment effects on behavioral/emotional reactivity and regulation.  
Stress-related processes, parenting quality, and maternal cognitive resources at ages 1, 2, and 3. To 
further assess the family stress pathway, information on maternal stress, mental health and interactions with 
children will be collected at child ages 1 and 2. Survey measures will assess family stress, chaos in the home, 
parenting beliefs and maternal symptoms of depression and anxiety. The videotaped free play and clean-up 
task at child age 2 will be coded for parental warmth and harshness. As a measure of maternal sensitivity, we 
will analyze mother and child synchrony in baseline cortisol levels, as well as in stress reactivity/recovery 
during the scary mask presentation described above (as the mother will observe her child’s distress during the 
task). Higher mother-child synchrony is linked to better attachment, language, and socioemotional 
competence,
152 and lower SES dyads tend to have reduced synchrony relative to higher SES counterparts.153 The 
NIH Toolbox Flanker test will be administered to mothers at child ages 2 and 3 to measure maternal cognitive 
resources (executive functioning, or “bandwidth”). Administrative data will enable us to track child welfare 
reports. Finally, data on preventive health care visits, including well-child and dental visits, will be collected via 
parent interview.  
Demographic characteristics. Baseline demographic measures, listed in Appendix 5, will be used to 
improve the precision of our experimental impact estimates and, in some cases, enable us to examine whether 
and how impacts vary by some of these key baseline characteristics. 
Long-term Follow-up. Although our 5-year window of research will enable us to collect data through 
age 3 and run basic impact and some moderation analyses, we will continue to engage in project activities 
beyond the end of our grant period. Since subject consent forms cover administrative data generated after age 
3, we plan to secure additional funding for subsequent collection and analyses of administrative data, including 
school records of target children and their siblings. The large number of family- and child-based measures 
collected in our age 2 home visits will be available for analysis 18 months prior to the end of our grant period, 
and will inform subsequent data collection strategies including the possibility of MRI-based measures of 
regional brain structure and function when the children are old enough to be assessed with this technique. 
Summary. Our team of neuroscientists, economists and developmental psychologists proposes the first 
experimental test of unconditional income transfers in the first years of life in the United States. Results will 
provide definitive evidence about the nature and magnitude of causal connections between family income and 
early neural, cognitive, and socio-emotional development. Beyond core contributions to both neuroscience and 
social science research, the proposed project will provide an unparalleled scientific foundation for the design of 
numerous tax and transfer policies aimed at low-income families with young children.  
 

 
Appendix 1: Flowchart Based on Pilot Study (launched July 2014) – Recruitment and Debit Cards 

Appendix 2: Demographics and Benefits Generosity by Site 
 
         
New York, NY   New Orleans, LA  Twin Cities, MN    Omaha, NE 
DEMOGRAPHICS 
20-mile 
radius 
50-mile 
radius 
20-mile 
radius 
50-mile 
radius 
20-mile 
radius 
50-mile 
radius 
20-mile 
radius 
50-mile 
radius 
Poverty (percentages show total population below the Federal Poverty Line) 
 
15.67%    13.30%    19.68%    17.24%    10.65%    10.27%    11.91%   12.35% 
Ethnic Distribution (percentages based on population below the Federal Poverty Line) 
Hispanic or Latino    
40.28%   38.53%    8.87%    7.09%    12.86%    12.18%    18.33%   16.28% 
Not Hispanic or Latino   59.72%    61.47%    91.13%    92.91%    87.14%   87.82%   81.67%   83.72% 
Racial Distribution (percentages based on population below the Federal Poverty Line) 
White 
37.00%   41.07%    28.83%   42.02%   52.01%    57.58%    61.89%   69.33% 
African American    
28.10%   26.29%   62.97%    51.25%   26.08%   22.54%    20.71%   15.70% 
Asian 
9.85%    9.47%    3.19%    2.10%    10.50%    9.00%    2.72%    2.97% 
American Indian or 
Alaska Native 
0.82%    0.77%    0.70%    0.80%    1.85%    1.95%    1.90%    1.70% 
Native Hawaiian or 
Pacific Islander 
0.04%    0.04%    0.13%    0.08%    0.04%    0.04%    0.08%    0.13% 
Other race 
20.86%   19.03%    2.68%    1.95%    4.07%    3.71%    7.30%    4.99% 
Two or more races    
3.32%    3.32%    1.50%    1.80%    5.36%    5.18%    5.41%    5.19% 
POLICY 
Number of Medicaid  Waivers Offered  
 
12 
8 
4 
7 
Average TANF Benefit Level (2015 annual maximum benefits for family of 3)  
 
$9,468 
$2,880 
$6,384 
$4,368 
COST OF LIVING 
Indices (percentage above or below the national COL of 100%)  
 
+116.7% 
-1.00% 
+11.0% 
-11.7% 
 
Demographics information from the American Community Survey  
Medicaid information from http://medicaidwaiver.org/ 
TANF information from http://www.cbpp.org/research/tanf-cash-benefits-have-fallen-by-more-than-20-
percent-in-most-states-and-continue-to-erode 
Cost of Living information from https://www.census.gov/compendia/statab/2012/tables/12s0728.pdf 
 
[Appendix 3 Omitted] 
 
 

Appendix 4: Child Outcome Measures (Note: not all of these outcomes are preregistered) 
 
 
 
Measure description 
 
Measure source a 
Administration 
time 
 
Psychometrics 
 
Wave b 
Language Development 
 
 
  Mean Length of Utterance 
Free-play interactions139 
20 minutes 
Very wide range across studies 
and ages (temporal reliability 
.61-.90+) 
2 
  Types and Tokens  
Free-play interactions139 
Varies (often self-paced 
by child) 
n/a 
2 
 Receptive Vocabulary: Picture 
Vocabulary 
NIH Toolbox168 
About 5 minutes 
Test-retest reliability .84 
Convergent validity .74 
3 
Memory 
 
 
 
 Declarative Memory: Picture Sequence 
Memory 
NIH Toolbox168 
About 5 minutes 
Test-retest reliability .76 
Convergent validity .59 
3 
Executive Function and Self-
Regulation 
 
 
 
 Flanker Inhibitory Control and 
Attention Test 
NIH Toolbox168 
About 5 minutes 
Test-retest reliability .95 
Convergent validity .70 
3 
  Dimensional Change Card Sort Test     NIH Toolbox168 
About 5 minutes 
Test-retest reliability .92 
Convergent validity .74 
3 
 Working Memory: List Sort Working 
Memory 
NIH Toolbox168 
About 5 minutes 
Test-retest reliability .87 
Convergent validity .64 
3 
 
 Preschool Self-Regulation Assessment  PSRA169 
About 30 minutes 
Internal consistency of assessor 
report 
(not full assessment) .82-.93 
3 
Socioemotional Processing     
 
 
 
 Behavioral coding of mother-toddler 
interaction  
Degnan et al.170,171 
10 minutes 
n/a 
2 
 
Social and emotional responsivity 
including fear, distress, 
anger/frustration, exuberance, 
persistence, activity level, inhibitory 
control 
LAB-TAB Preschool 
version115 
10 minutes    
Internal consistency .50-.95    
3 
  Externalizing/internalizing behavior 
Brief Infant–Toddler Social 
and Emotional Assessment 
(BITSEA)
117 
7-10 minutes 
Test-retest reliability .87 
Internal consistency .65-.79 
3 

Pre-Academic Skills 
 
 
 
  Brief Literacy  
Woodcock-Johnson172 
About 5 minutes    
Reliability .80-.90+ 
3 
  Brief Math 
Woodcock-Johnson172 
About 5 minutes    
Reliability .80-.90+ 
3 
IQ 
 
 
 
  Mental Development Index 
Bayley Scales of Infant and 
Toddler Development173 
About 30 minutes 
Reliability .86-.93 
Specificity .77-1.00 
2 
  WPPSI-IV 
WPPSI-IV
174 
30-45 minutes 
Internal consistency .95 
Test-retest reliability .86-.92 
3 
Brain Function and Connectivity     
 
 
 
EEG: resting brain function (power, an 
index of cortical activation reflecting 
synchronous post-synaptic currents 
within a local neuronal population, 
and coherence, a measure reflecting 
synchronization of oscillatory EEG 
activity between electrode sites, 
serving as a putative measure of 
functional connectivity) 
Marshall et al 2002132 
About 10 minutes 
n/a 
3 
 
ERP: language (comparison of brain 
activity to known words vs. unknown 
words) 
Zangl & Mills (2007)175 
 
About 5 minutes  
n/a 
3 
 
ERP: memory (comparison of brain 
activity to previously-seen vs. novel 
faces) 
Nelson & Collins (1991)135    
About 5 minutes 
n/a 
3 
Health and Development 
 
 
 
 Well-baby visits, illness, diagnoses and 
medications, injuries 
MetroBaby176 
About 5 minutes 
n/a 
1, 2, 3 
  Developmental milestones 
Ages and Stages 
Questionnaire (ASQ)177 
10-15 minutes 
Sensitivity .86 
Specificity .85 
1,2,3 
  Body Mass Index (BMI) 
CDC 
About 2 minutes 
n/a 
3 
School Achievement 
 
 
 
 School test scores for target children 
and siblings 
Administrative data 
 
 
ages 5+ 

a Source of item indicates a recent survey or study with comparable samples that administered the item. When not available, source indicates the 
primary authors of the scale or item. MetroBaby=NYU Center for Research on Culture, Development, and Education Birth Cohort Study, see 
www.steinhardt.nyu.edu/crcde/projects/childhood; NIH Toolbox= Northwestern University and NIH, see www.nihtoolbox.org; NCS=National 
Children’s Study, see http://www.nationalchildrensstudy.gov/research/workshops/Pages/U-Minnesota-formative-ncs-research-day-
2011.pdf 
b 1 = age 1 phone interview, 2 = age 2 home visit, 3 = age 3 lab visit; administrative data are gathered continuously and will be accessed shortly before 
they will be analyzed. 

Appendix 5: Measures of Maternal and Family Processes and Characteristics  (Note: not all of 
these measures are preregistered) 
 
Measure description 
Item source 
a    
Wave  b 
Household Economic Behavior 
 Household income: total earnings, total from social assistance and 
related programs 
MTO178 and admin data 
H, 1,2,3 
 
Household size: roster of every person residing in the household, 
relationship to the infant, age, sex 
MTO178 
H, 1,2,3 
 
Indicators of economic stress: utility cutoffs, eviction, missed 
payments, untreated health conditions 
MTO178 
H, 1, 2, 3 
 
Food insufficiency: less than desired amount of food, type of food, 
skipped meals 
MTO178 
H, 1, 2, 3 
 
Household expenditures: rent/mortgage, utilities, transportation 
costs, alcohol, drugs, cigarettes 
MetroBaby176 
H, 1, 2, 3 
 Net worth: formal and informal debt, any assets/savings 
MTO178 
H, 3 
Housing and Neighborhoods 
 Perceptions of neighborhood safety: safety, victimization    
MTO178 
H, 1, 2 
 
Neighborhood poverty: Census data on percent poor in the 
neighborhood 
Census 
H, 1, 2, 3 
 Housing quality: crowding/number of rooms, type of housing, 
housing problems 
MTO178 
1, 2, 3 
 
Residential mobility: number of moves in recent past, whether 
voluntary/involuntary 
MTO178 
1, 2, 3 
Parental Employment  
 Parental work histories and schedules: total hours (full or part 
time), number of jobs, days worked, regularity of work schedule 
MetroBaby,176 MTO,178 admin 
data 
H, 1, 2, 3 
Nonparental Care 
 
Nonparental care experiences: number and type of providers, 
hours in care, regularity of care, qualities of care 
NSECE 
1, 2, 3 
Maternal Relationships 
 
Mother’s romantic relationships: marital status, relationship 
quality with biological father and/or other romantic partner, 
presence of domestic violence 
MetroBaby,176 CDC 
H, 1, 2, 3 
Home Environment 
 
Child-related enrichment expenditures: children's books and 
toys, out-of-pocket nonparental care 
MetroBaby176 
1,2, 3 
 Parent-child interaction and environment: Infant/Toddler 
HOME Inventory (stimulating toys and activities, home organization)  Caldwell & Bradley179 
2 
 
Parent-child language: mean length of utterance, types and 
tokens from videotaped interaction (free play and clean-up task) 
Matas et al.180 
2 
 Chaos in the home: Home Environment Chaos Scale 
Evans181 
H, 1, 2, 3 

 
Parental Stress 
 Family stress: parenting-related stressors  
Fragile Families182 
1, 2, 3 
 General stress: Perceived Daily Stress Scale 
Cohen & Williamson183  
1, 2, 3 
 Maternal hair cortisol: index of chronic stress 
1 measure138,65,141,142 
2 
 Maternal salivary cortisol: index of acute stress 
3 measures100,133-136,184-193 
2 
   Maternal cognitive resources  (“bandwidth”): Flanker 
Inhibitory Control and Attention Test 
NIH Toolbox168 
2, 3 
 Child protective services: maltreatment investigations and 
substantiations 
Admin data 
H, 1, 2, 3 
Maternal Health 
 Physical health: general health, pregnancy, contraception    
MetroBaby176 
H, 1, 2, 3 
 Mental health: depression, anxiety 
PHQ-9
194, Beck
195 
H, 1, 2 ,3 
Child Stress 
 Child hair cortisol: index of chronic stress 
1 measure
66,140,141 
2 
 Child salivary cortisol: index of acute stress 
3 measures100,133-136,184-193 
2 
Demographic Characteristics 
 Maternal and paternal education 
 
H, 1, 2, 3 
 Race 
 
H 
 Ethnicity 
 
H 
 Country of origin 
 
H 
 Language(s) spoken in the home 
 
H, 1, 2, 3 
 Birth weight 
 
H 
 Parity 
 
H 
a Source of item indicates a recent survey or study with comparable samples that administered the item. When not 
available, source indicates the primary authors of the scale or item. MTO=Moving to Opportunity study, see 
www.mtoresearch.org; MetroBaby=NYU Center for Research on Culture, Development, and Education Birth Cohort 
Study, see www.steinhardt.nyu.edu/crcde/projects/childhood; NSECE=National Survey of Early Education and 
Care, see http://www.acf.hhs.gov/programs/opre/research/project/national-survey-of-early-care-and-
education-nsece-2010-2014 
b H = hospital at birth, 1 = age 1 phone interview, 2 = age 2 home visit, 3 = age 3 lab visit; administrative data are gathered 
continuously and will be accessed shortly before they will be analyzed. 

Appendix 6: Conceptually-Related Family Processes 
 
FAMILY INVESTMENT PATH WAY MEASURES 
 
Economic wellbeing 
Household income 
Indicators of economic hardship 
Food insufficiency 
Assets and debt 
Total household expenditures 
Neighborhood quality 
Neighborhood poverty 
Perceptions of neighborhood safety (safety, victimization) 
Housing quality 
Crowding/number of rooms 
Type of housing 
Housing problems 
Child-related enrichment expenditures 
Children's books and toys 
Out-of-pocket nonparental care 
Parent-child interaction and environment 
Infant/Toddler HOME Inventory (stimulating toys and activities, home organization)  
Parent-child language 
Mean length of utterance 
Types and tokens from videotaped interaction (free play and clean-up task) 
 
FAMILY STRESS PATH WAY MEASURES 
 
Family stress 
Chaos in the home 
Parental stress index 
Family stress index 
Maternal hair cortisol 
Maternal salivary cortisol 
Mother’s health and resources 
Maternal physical health 
Maternal mental health 
Maternal cognitive resources (“bandwidth”) 
Sensitivity of parenting  
Parental warmth as indexed on the Infant/Toddler HOME Inventory 
Child protective services 
Synchronicity of maternal and child cortisol reactivity 
Child stress measures 
Child hair cortisol 
Child salivary cortisol 
      
RELATED FAMILY PROCESSES  
 
Parental work histories and schedules: total hours (full or part time), number of jobs, days worked, 
regularity of work schedule 
Nonparental care experiences: number and type of providers, hours in care, regularity of care, qualities of 
care 
Maternal romantic relationships: marital status, relationship quality with biological father and/or other 
romantic partner, presence of domestic violence 
 

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