Downloaded from http://journals.lww.com/jrnldbp by BhDMf5ePHKav1zEoum1tQfN4a+kJLhEZgbsIHo4XMi0hCywCX1AWnYQp/IlQrHD3i3D0OdRyi7TvSFl4Cf3VC4/OAVpDDa8K2+Ya6H515kE= on 04/14/2022
Downloadedfromhttp://journals.lww.com/jrnldbp by BhDMf5ePHKav1zEoum1tQfN4a+kJLhEZgbsIHo4XMi0hCywCX1AWnYQp/IlQrHD3i3D0OdRyi7TvSFl4Cf3VC4/OAVpDDa8K2+Ya6H515kE= on 04/14/2022
See the Video Abstract at www.jdbp.org
Maternal Stress and Early Neurodevelopment: Exploring the
Protective Role of Maternal Growth Mindset
Mei Elansary, MD,* Lara J. Pierce, PhD,†Wendy S. Wei, MEd,‡Dana Charles McCoy, PhD,‡
Barry Zuckerman, MD,* Charles A. Nelson, PhD†
ABSTRACT: Objective: The purpose of this study was to test associations between maternal stress,
maternal mindset, and infant neurodevelopment at 12 months of age. Specifically, we sought to examine the
extent to which maternal growth mindsets may serve to attenuate the negative associations between maternal
stress and infants’ neurodevelopment. Methods: The current exploratory study leverages data from a longitudinal
cohort study following mother-infant dyads. Maternal-perceived stress, maternal mindset, and infant electroen-
cephalography (EEG) recordings were collected when infants were 12 months of age. The final analytic sample
included 33 dyads. Results: Results revealed no statistically significant main effects of maternal stress or
maternal mindset for any of the infant EEG frequency band outcomes. After including interactions between
maternal stress and mindset, statistically significant positive interactions were detected for all EEG frequency
bands. Simple slope tests revealed significant negative associations between maternal stress and each of the 6
EEG frequency bands for mothers with more fixed-oriented mindsets. Associations between maternal stress and
infant EEG outcomes for mothers with more growth-oriented mindsets did not differ from 0. Conclusion: These
findings suggest that infants raised by mothers with growth mindsets may be protected against the neuro-
developmental consequences of higher maternal stress.
(J Dev Behav Pediatr 43:e103–e109, 2022) Index terms: EEG, infancy, neurodevelopment, stress.
Exposure to adversity in the first years of a child’s life
greatly elevates the risk of lifelong problems in learning,
behavior, and health.
One prevalent form of early
childhood adversity is exposure to maternal stress,
which often co-occurs with other family adversities
and may compromise the frequency and/or quality of
Children of mothers experi-
encing poor mental health are at particular risk for neg-
ative developmental outcomes
and alterations in
developing physiologic and neural systems.
research has demonstrated associations between mater-
nal stress and infants’brain activity inferred from elec-
troencephalography (EEG). At 2 months of age, infants
whose mothers reported higher levels of perceived stress
had lower absolute beta and gamma spectral power
12-month-old infants whose mothers had higher physio-
logic stress were found to have reduced relative alpha and
high gamma power.
Importantly, such altered patterns of
EEG activity can persist throughout childhood
been associated with developmental delays and problems
with learning and attention.
Overall, these findings
suggest the susceptibility of the developing nervous system
to maternal stress and highlight the potential of EEG as a
tool to examine the consequences of maternal-infant psy-
Evidence also suggests that the negative de-
velopmental effects of psychosocial risk exposure can be
mitigated by responsive and contingent caregiving.
However, little work to date has explored whether
protective factors, particularly those related to the nature
of parent-child interactions, might act to buffer stress-
related alternations in infant neurodevelopment, specif-
ically. One factor that may directly shape parents’inter-
actions with their children is their beliefs about whether
intelligence is fixed or malleable, referred to as fixed or
growth mindset, respectively.
growth mindsets report that they are more likely to en-
gage in literacy and math activities with their preschool-
age children compared with parents with a
Recent studies using EEG have shed
light on underlying cognitive processes associated with
From the *Department of Pediatrics, Boston University School of Medicine,
Boston Medical Center, Boston, MA. This work was completed when Dr.
Elansary was a member of the Division of Developmental Medicine at Boston
Children’s Hospital; †Division of Developmental Medicine, Boston Children’s
Hospital and Harvard Medical School, Harvard University, Boston, MA; ‡Harvard
Graduate School of Education, Cambridge, MA.
Received February 2021; accepted July 2021.
Support for this research was provided by grant 1025 from the JPB Foundation-
funded Research Network on Toxic Stress and Health (C. A. Nelson) and Boston
Children’s Hospital Developmental Medicine Seed Funding (M. Elansary).
Disclosure: The authors declare no conflict of interest.
Supplemental digital content is available for this article. Direct URL citations
appear in the printed text and are provided in the HTML and PDF versions of this
article on the journal’s Web site (www.jdbp.org).
Address for reprints: Mei Elansary, MD, Division of General Pediatrics, Boston
University School of Medicine, 801 Albany St, Boston, MA 02118; e-mail: mei.
Copyright Ó2021 Wolters Kluwer Health, Inc. All rights reserved.
Vol. 43, No. 2, February/March 2022 Visit jdbp.org | e103
Copyright © 2021 Wolters Kluwer Health, Inc. Unauthorized reproduction of this article is prohibited.
growth mindset, including an enhanced ability to moni-
tor and learn from errors in laboratory-based tasks.
Emerging work also suggests that interventions tar-
geting growth mindsets may have positive downstream
effects on multiple outcomes. Several large-scale, school-
based studies, for example, have demonstrated positive
impacts on high-school students’academic achieve-
Furthermore, laboratory-based and field-based
intervention studies have demonstrated that encouraging
parents to hold growth mindsets (e.g., educating them
regarding the malleability of their children’s abilities and
their own role in promoting learning) have positive im-
pacts both on parent behavior and on child outcomes,
particularly for children whose parents initially believed
their child’s abilities were fixed.
intervention work has focused on preschool-age
studies with parents of infants
are emerging. A growth mindset intervention for parents
of 10-month-olds increased both parent and child use of
pointing, once again demonstrating stronger effects for
dyads where parents endorsed fixed mindsets at base-
line. The intervention also resulted in increased vocab-
ulary growth from 10 to 18 months of age for children
whose parents initially endorsed fixed mindsets when
compared with fixed-mindset parents in the control
Overall, this evidence suggests that
parent mindset is an important avenue of future in-
vestigation, especially during infancy, given implications
for parent-child interactions and related interventions.
This study extends previous work relating maternal
stress to child neurodevelopment to explore the pro-
tective role of maternal growth mindsets. In particular,
these exploratory analyses seek to examine the extent to
which maternal growth mindsets may serve to attenuate
the negative association between maternal stress and
children’s neurodevelopment in the first year of life, as
measured using EEG at 12 months of age. We hypothe-
size that the negative relation between maternal stress
and infant neurodevelopment will be less pronounced
for infants whose mothers report a growth mindset rel-
ative to those reporting a fixed mindset. Building on
previous research, we predict maternal reports of stress
to be negatively associated with high-frequency power
(beta and gamma), in particular, and that maternal
growth mindset may attenuate this negative association.
By addressing this question, we aim to extend the liter-
ature on early childhood adversity to consider the neu-
rodevelopmental outcomes of parental stress and to
identify a potential protective factor to be targeted in
Sample and Procedure
This study leverages data from a longitudinal cohort
study following mother-infant dyads (N 559 enrolled at
2 months) to investigate child responses to early adver-
Participants were recruited from a primary care
clinic serving predominately publicly insured children in
Boston, MA. Exclusion criteria were mothers of children
with gestational age younger than 37 weeks; identified
genetic, metabolic, or neurologic disorders; uncorrected
vision difficulties; or birth-related complications. Written
informed consent was provided by parents or guardians
for all participants. The Institutional Review Board of the
local institution approved all procedures.
For this exploratory study, mothers were asked to
complete a scale measuring maternal mindset at the 12-
month study visit (N 549), when infants were 12
months of age on average. Forty-one mothers completed
the mindset scale because of later introduction of the
measure; of the 41 dyads with data on maternal mindset,
8 were excluded because of missing data on at least 1 of
the primary study variables and/or for not passing the
data quality check for electroencephalography (EEG)
data. The final analytic sample, therefore, included 33
mother-infant dyads. The magnitude of sample attrition
for the parent study (16.9% of participants not present-
ing to the 12-month study visit) and loss of some data for
not passing the data quality check for EEG is typical for
longitudinal cohort EEG samples enrolling infants.
fants and mothers in the analytic sample were largely
similar to those in the excluded sample (Supplemental
Table 1, Supplemental Digital Content 1, http://links.
lww.com/JDBP/A314). Only 1 significant difference
emerged: Mothers in the excluded sample had more
growth-oriented mindsets than mothers in the analytic
Demographic information including maternal educa-
tion (Table 1) was collected from families at study en-
rollment when infants were 2 months of age on average
and confirmed at the 12-month visit when maternal-
perceived stress and mindset were ascertained.
Maternal-perceived stress at 12 months was assessed us-
ing the validated and normed 10-item Perceived Stress
Scale, which measures stress on a 5-point scale; items are
summed, and total scores range from 0 to 40.
showed high internal consistency in the sample (a5
0.84). Maternal mindset was measured with Dweck'
Theories of Intelligence (TOI) scale, which consists of 8
self-reported questions on a 6-point scale that measure
the extent to which participants believe intelligence is
fixed or malleable. The questionnaire includes 4 fixed-
oriented statements (e.g., You have a certain amount
of intelligence and you can’t really do much to change
it) and 4 growth-oriented statements that were reverse
coded (e.g., No matter who you are, you can signifi-
cantly change your intelligence level). Items were av-
eraged to calculate participants’final TOI scores, which
were centered and coded such that positive scores (0–3)
reflect more growth-oriented mindsets and negative
scores (23 to 0) reflect more fixed-oriented mindsets.
The scale showed adequate internal consistency in this
e104 Maternal Stress, Early Neurodevelopment, and Growth Mindset Journal of Developmental & Behavioral Pediatrics
Copyright © 2021 Wolters Kluwer Health, Inc. Unauthorized reproduction of this article is prohibited.
Infant EEG recordings were completed at approximately
12 months (mean 512.53; SD 50.48 months) using a 128-
Channel HydroCel Sensor Net System (EGI Inc); full details
of the EEG protocol have been previously published.
fants were positioned 60 cm from a computer monitor
facing forward on their parent’s lap while they viewed a
videoofmovingchildren’s toys for up to 5 minutes. A
trained researcher engaged minimally with the infant, using
a rain stick toy and bubbles to redirect the infant’sattention
toward the screen only when necessary.
EEG reflects the summation of postsynaptic potentials
from large synchronous populations of neurons. The
EEG signal is composed of rhythmic oscillatory activity
that falls into a range of characteristic frequencies (delta,
theta, alpha, beta, and gamma). In both adults and chil-
dren, these component frequency bands are believed to
be functionally distinct. For example, alpha rhythms
have been implicated in visual attention (among other
processes) while gamma oscillations are believed to play
a role in sensory processing and perceptual binding.
Although EEG can be measured from infancy, consider-
able developmental changes in EEG patterns can be ob-
served over time. As brain activity becomes more
synchronous and organized from infancy into early
childhood, absolute power (amount of activity) tends to
increase across all frequency bands. At the same time,
the relative contribution of power in low-frequency
bands (e.g., delta and theta) has been found to
decrease while the relative contribution of power in
high-frequency bands (e.g., beta and gamma) increases.
This pattern of maturational change is linked to the de-
velopment of increasingly complex cognitive out-
For example, higher absolute spectral power,
particularly in high-frequency bands (e.g., beta and
gamma), has been associated with better cognitive out-
comes in childhood.
By contrast, a pattern of low rel-
ative high-frequency and high relative low-frequency
power has been observed after exposure to stress and
psychosocial adversity, and some explanations suggest
that this pattern reflects maturational lag.
Raw EEG data files were exported from NetStation
4.5.4 in MATLAB file format (MathWorks, Inc) and pre-
processed using the Harvard Automated Processing Pipe-
line for Electroencephalography,
an automated EEG
processing pipeline optimized for use with infant data and
used with MATLAB, version 2014b, and EEGLab, version
Details regarding channel selection, artifact
correction, and power spectra extraction have been pre-
-transformed absolute whole-
brain power was calculated for each frequency band of
interest as follows: d(2–4Hz),u(4–6Hz),lowa(6–9Hz),
high a(9–13 Hz), b(13–30 Hz), and g(30–50 Hz). In
addition, relative power was calculated as absolute power
in each frequency band divided by total power.
All statistical analyses were conducted in Stata (Ver-
To examine associations between reported
maternal stress, maternal mindset, and infant EEG power,
a series of multiple regression analyses were conducted.
Table 1. Descriptive Statistics (N 533 Children)
M/% SD Min Max
Maternal stress (PSS) 12.42 6.84 0.00 26.00
Maternal mindset (TOI) 0.29 1.03 22.38 2.00
Infant age (in months) 12.53 0.48 11.77 14.13
Infant sex (female) 48%
Infant birthweight (in pounds) 7.04 1.13 4.11 9.56
Infant race/ethnicity: Black 47%
Infant race/ethnicity: Latino/a 28%
Maternal age (in years) 28.88 5.32 20.00 39.00
Maternal education: less than high school diploma 9%
Maternal education: high school diploma or equivalent 48%
Maternal education: associates degree or more 42%
Absolute dpower 0.17 0.14 20.11 0.44
Absolute upower 20.09 0.15 20.33 0.21
Absolute low apower 0.11 0.16 20.15 0.40
Absolute high apower 0.09 0.13 20.20 0.33
Absolute bpower 0.56 0.13 0.27 0.81
Absolute gpower 0.46 0.13 0.10 0.67
PSS, Mother-reported Perceived Stress Scale; TOI, Theory of Intelligence (centered at 3 on the original scale and reverse-coded so that positive scores reflect more growth-oriented mindset).
Vol. 43, No. 2, February/March 2022 Copyright Ó2021 Wolters Kluwer Health, Inc. All rights reserved. e105
Copyright © 2021 Wolters Kluwer Health, Inc. Unauthorized reproduction of this article is prohibited.
For each EEG frequency band, we ran 2 models (1) in-
cluding maternal-perceived stress and mindset as pre-
dictors of EEG power and (2) including an additional
interaction between perceived stress and mindset to test
whether associations between maternal-perceived stress
and EEG power would differ based on maternal mindset
patterns. Simple slope tests were also used to examine
whether associations between maternal stress and EEG
power for mothers with more fixed-oriented mindsets
and those with more growth-oriented mindsets
differed significantly from 0. Specifically, fixed and
growth mindset were represented by prototypical values
on the recoded TOI scale (i.e., 21 and 11, respectively).
In all analyses, the following demographic factors were
included as covariates: infant age (in months), infant sex
(1 5female), maternal educational attainment (1 5as-
sociate’s degree or more), and infant race/ethnicity (in-
dicators for Black/African-American and Latino/a). See
Supplemental Table 2 (Supplemental Digital Content 2,
http://links.lww.com/JDBP/A315) for correlations be-
tween primary study measures.
As previously noted, participants were excluded be-
cause of missing data on any of primary predictors
(maternal-perceived stress and mindset) or outcomes
(EEG power). Among covariates, 1 child (3%) was miss-
ing data on infant age, and 2 children (6%) were missing
data on race/ethnicity. Multiple imputation by chained
equations was used to generate 10 data sets to account
for these missing covariates.
Full demographic information is provided in Table 1.
There was heterogeneity in maternal education such that
48% of mothers reported completing high school or
equivalent, and 42% reported obtaining an associate’sde-
gree or higher. Forty-seven percent of infants were Black,
28% were Latino/a, and 25% were either White or another
race/ethnicity. When infants were 12 months old, the mean
maternal age was 28.88 years (SD 55.32; range 520–39).
Associations Between Maternal Stress, Maternal
Mindset, and Infant EEG Power
Results revealed no statistically significant main ef-
fects of maternal stress or maternal mindset for any of
the infant electroencephalography (EEG) frequency
band outcomes (Table 2). After including interactions
between maternal stress and mindset, statistically signif-
icant positive interactions were detected for all EEG
frequency bands (b50.008–0.011, SE 50.004–0.005, p
,0.05; Table 2 and Supplemental Table 3, Supplemental
Digital Content 3, http://links.lww.com/JDBP/A316). For
illustrative purposes, interactions were graphed for 1
low-frequency band and 1 high-frequency EEG band
(Figs. 1A and B).
Table 2. Results from Predicting Absolute EEG Power at 12 Months (N 533 Children)
duLow aHigh abg
PSS 20.001 (0.004) 20.006 (0.005) 0.002 (0.005) 20.005 (0.005) 20.000 (0.005) 20.007 (0.005) 20.003 (0.004) 20.008 (0.005)
20.002 (0.004) 20.008 (0.004)
20.002 (0.004) 20.007 (0.004)
TOI 0.011 (0.030) 20.007 (0.030) 0.017 (0.032) 20.006 (0.030) 0.008 (0.034) 20.012 (0.033) 20.003 (0.028) 20.020 (0.028) 20.012 (0.027) 20.029 (0.026) 20.018 (0.028) 20.034 (0.027)
PSS 3TOI 0.009 (0.004)
20.027 (0.068) 20.088 (0.071) 20.027 (0.070) 20.101 (0.071) 20.062 (0.075) 20.128 (0.078) 20.059 (0.061) 20.114
(0.065) 20.047 (0.059) 20.103 (0.061) 20.045 (0.059) 20.098 (0.063)
0.056 (0.062) 0.071 (0.059) 0.033 (0.066) 0.052 (0.060) 0.060 (0.069) 0.077 (0.065) 0.061 (0.058) 0.075 (0.055) 0.074 (0.056) 0.088 (0.052) 0.081 (0.057) 0.094 (0.054)
0.020 (0.082) 0.054 (0.079) 0.039 (0.086) 0.079 (0.081) 0.074 (0.089) 0.110 (0.087) 0.056 (0.075) 0.087 (0.073) 0.048 (0.071) 0.079 (0.068) 0.039 (0.071) 0.069 (0.069)
0.011 (0.094) 0.006 (0.088) 0.004 (0.099) 20.003 (0.090) 20.008 (0.101) 20.014 (0.095) 0.006 (0.085) 0.001 (0.080) 20.041 (0.082) 20.046 (0.077) 20.022 (0.084) 20.027 (0.079)
20.038 (0.070) 20.051 (0.066) 20.022 (0.074) 20.038 (0.067) 20.001 (0.078) 20.015 (0.073) 20.037 (0.065) 20.049 (0.062) 20.046 (0.062) 20.057 (0.059) 20.007 (0.064) 20.019 (0.060)
Constant 0.162 (0.028)
0.088 0.254 0.088 0.313 0.133 0.291 0.137 0.289 0.153 0.314 0.117 0.260
Results are reported in unstandardized coefficients and standard errors in parentheses; 1p,0.10, *p,0.05, **p,0.01, ***p,0.001. EEG, electroencephalography; PSS, Mother-reported Perceived Stress Scale; R/E, race/ethnicity; TOI, Theory of Intelligence (centered at 3 on the original scale and reverse-coded so that positive scores reflect more
Maternal education is an indicator where 1 is equal to a mother attending school beyond high school.
e106 Maternal Stress, Early Neurodevelopment, and Growth Mindset Journal of Developmental & Behavioral Pediatrics
Simple slope tests were used to probe the nature of
interaction, as is common in moderation analyses. A
simple slope is defined as the regression of the outcome
y (EEG power) on the predictor X (maternal stress) at a
specific value of the moderator z (fixed vs
growth mindset). It is common to select values that are 1
SD above and below the mean or values that represent
Simple slope tests revealed that the
associations between maternal stress and each of the 6
EEG frequency bands for mothers with more fixed-
oriented mindsets (theories of intelligence [TOI] 521)
were negative and significantly different from 0 (p5
0.03–0.07; Supplemental Table 4, Supplemental Digital
Content 4, http://links.lww.com/JDBP/A317). However,
the associations between maternal stress and infant EEG
outcomes for mothers with more growth-
oriented mindsets (TOI 51) did not differ from 0 (p5
ns). These findings collectively suggest that mothers’
more growth-oriented mindset may buffer the negative
associations between maternal stress and children’s EEG
outcomes. Additional ad hoc analyses also revealed that
at low levels of maternal stress (i.e., 1 SD below the
sample average), levels of absolute EEG power were
significantly higher for more fixed-oriented mothers than
for more growth-oriented mothers for the u, high a,b,
and gfrequency bands; however, at high levels of ma-
ternal stress (i.e., 1 SD above the sample average), levels
of absolute EEG power were significantly higher for
growth-oriented mothers for the ufrequency band (p5
0.08; Supplemental Table 5, Supplemental Digital Con-
tent 5, http://links.lww.com/JDBP/A318). Finally, no as-
sociations with relative EEG power were detected in our
models (Supplemental Table 6, Supplemental Digital
Content 6, http://links.lww.com/JDBP/A319).
Previous research has shown that elevated levels of
maternal stress—both perceived
have been correlated with alterations in neuro-
development for infants. The results of this study sug-
gest, however, that these associations between maternal
stress and child neurodevelopment may vary based on
other factors. Specifically, we find that infants raised by
mothers with growth mindsets may be protected against
the neurodevelopmental consequences of higher mater-
nal stress. In particular, for children whose mothers en-
dorsed growth mindsets, there was no difference in
electroencephalography (EEG) outcomes based on
mothers’perceived stress levels. Yet, for mothers who
endorsed fixed mindsets, infant EEG power was signifi-
cantly lower when mothers reported high (vs low) levels
of stress. Collectively, these results suggest that maternal
stress may only be harmful for infant neurodevelopment
in the context of maternal beliefs of lack of control over
their children’s outcomes.
Inspection of Figure 1 (and Supplemental Table 5,
Supplemental Digital Content 5, http://links.lww.com/
JDBP/A318) also reveals the somewhat counterintuitive
finding that among children with lower-stress mothers (i.
e., those with perceived stress below the sample mean),
those whose mothers endorsed a fixed mindset had
higher EEG power on 4 of the 6 outcomes tested relative
to those whose mothers endorsed a growth mindset.
These findings suggest that although the protective ef-
fects of growth mindset may not be apparent at low
levels of stress, the potential benefits of maternal
growth mindset are particularly relevant in settings of
high maternal stress. Overall, these findings highlight the
need for additional research to contextualize the cir-
cumstances under which various risk and protective
factors may exert their influence.
To our knowledge, this is the first study to examine
(1) links between infant brain function and
maternal mindset and (2) the role of mindset in the
context of maternal stress. Preliminary results suggest
that growth mindset can be a protective factor for
maternal-infant dyads with high stress and a potential
target for future interventions aiming to foster neuro-
development in the first year of life. In particular,
Figure 1. Interaction between maternal stress and mindset predicting 1 low-frequency EEG band (A: theta) and 1 high-frequency EEG band (B: beta).
Higher absolute spectral power, particularly in high-frequency bands (e.g., b), has been associated with better cognitive outcomes in childhood. Low/
high maternal stress is represented by 1 SD below/above the sample average, respectively. Fixed-oriented and growth-oriented mindsets are represented
by prototypical values on the theory of intelligence scale, which are equal to 21 and 11 on our recoded scale, respectively. EEG, electroencepha-
Vol. 43, No. 2, February/March 2022 Copyright Ó2021 Wolters Kluwer Health, Inc. All rights reserved. e107
previous work has demonstrated that parents can be
trained to hold growth mindsets rather than
fixed mindsets through relatively simple messaging, with
positive impacts on parent interactions and child learn-
This study suggests that promoting
growth mindset among mothers of infants may mitigate
the negative impact of maternal psychosocial stress on
developmental trajectories. Future work should examine
potential mechanisms that mediate the protective effect
of growth mindset, including responsive maternal-child
interactions. In addition, there is a need for interventions
that not only shape parents’growth mindsets but also
encourage related parenting behaviors that have been
demonstrated to promote a growth mindset among
children, such as parental praise of children’s effort.
Although this exploratory study provides important
novel evidence concerning the moderating role of
stress, it is also limited in several important ways. First,
maternal-perceived stress, mindset, and infant EEG were
examined at a single time point (12 months). While it is
assumed that mindset is a stable psychological entity-absent
intervention, our study cannot establish the temporal pre-
cedence of our variables. Future studies should examine
whether and how parenting mindset changes over the
course of infant development, how parent mindset may
vary across domains (e.g., child intelligence and health),
and how these may also relate to changes in maternal stress
and infant neurodevelopment. Second, our findings rely on
maternal reports of stress rather than physiologic markers
of maternal stress. Future studies may also benefit from
direct measures of stress in the infant. Finally, it will be
important to replicate this study with a larger and more
representative sample and with short-term and long-term
behavioral and cognitive outcomes.
These exploratory analyses suggest that maternal
growth mindset is a protective factor that may mitigate
previously demonstrated negative effects of maternal
stress on child neurodevelopment. These findings pro-
vide a promising framework for fostering infant well-
being among vulnerable maternal-child dyads.
1. Felitti VJ, Anda RF, Nordenberg D, et al. Relationship of childhood
abuse and household dysfunction to many of the leading causes of
death in adults. The Adverse Childhood Experiences (ACE) Study.
Am J Prev Med. 1998;14:245–258.
2. Bailey R, Mokonogho J, Kumar A. Racial and ethnic differences in
depression: current perspectives. Neuropsychiatr Dis Treat. 2019;
3. Horwitz SM, Briggs-Gowan MJ, Storfer-Isser A, et al. Prevalence,
correlates, and persistence of maternal depression. J Womens
Health (Larchmt). 2007;16:678–691.
4. Lorant V, Deliege D, Eaton W, et al. Socioeconomic inequalities in
depression: a meta-analysis. Am J Epidemiol. 2003;157:98–112.
depression and associated adversity on early mother-infant interactions
and later infant outcome. Child Dev. 1996;67:2512–2526.
6. England MJ, Sim L. Depression in Parents, Parenting, and Children:
Opportunities to Improve Identification, Treatment, and Prevention.
Institute of Medicine Committee onDepressionPPatHDoC;2009.
7. Hammen C, Gordon D, Burge D, et al. Maternal affective disorders,
illness, and stress: risk for children’s psychopathology. Am J
8. Sharp D, Hay DF, Pawlby S, et al. The impact of postnatal
depression on boys’intellectual development. J Child Psychol
9. Lesesne CA, Visser SN, White CP. Attention-deficit/hyperactivity
disorder in school-aged children: association with maternal mental
health and use of health care resources. Pediatrics. 2003;111:
10. Shonkoff JP, Garner AS; Committee on Psychosocial Aspects of
Child and Family Health; Committee on Early Childhood, Adoption,
and Dependent Care; Section on Developmental and Behavioral
Pediatrics. The lifelong effects of early childhood adversity and
toxic stress. Pediatr Dent. 2012;129:e232–e246.
11. Bick J, Nelson CA. Early adverse experiences and the developing
brain. Neuropsychopharmacol. 2016;41:177–196.
12. Pierce LJ, Thompson BL, Gharib A, et al. Association of perceived
maternal stress during the perinatal period with
electroencephalography patterns in 2-month-old infants. JAMA
13. Troller-Renfree SV, Brito NH, Desai PM, et al. Infants of mothers
with higher physiological stress show alterations in brain function.
Dev Sci. 2020;23:e12976.
14. Vanderwert RE, Marshall PJ, Nelson CA III, et al. Timing of
intervention affects brain electrical activity in children exposed to
severe psychosocial neglect. PLoS One. 2010;5:e11415.
15. Brito NH, Fifer WP, Myers MM, et al. Associations among family
socioeconomic status, EEG power at birth, and cognitive skills
during infancy. Dev Cogn Neurosci. 2016;19:144–151.
16. Corning WC, Steffy RA, Anderson E, et al. EEG “maturational lag”
profiles: follow-up analyses. J Abnorm Child Psychol. 1986;14:235–
17. McLaughlin KA, Fox NA, Zeanah CH, et al. Delayed maturation
in brain electrical activity partially explains the association
between early environmental deprivation and symptoms of
attention-deficit/hyperactivity disorder. Biol Psychiatry. 2010;
18. Bick J, Zhu T, Stamoulis C, et al. Effect of early institutionalization
and foster care on long-term white matter development: a
randomized clinical trial. JAMA Pediatrics. 2015;169:211–219.
19. Mueller C, Rowe ML, Zuckerman B. Mindset matters for parents
and adolescents. JAMA Pediatr. 2017;171:415–416.
20. Moorman EA, Pomerantz EM. Ability mindsets influence the quality
of mothers’involvement in children’s learning: an experimental
investigation. Dev Psychol. 2010;46:1354–1362.
21. Muenks K, Miele DB, Ramani GB, et al. Parental beliefs about the
fixedness of ability. J Appl Dev Psychol. 2015;41:78–89.
22. Schroder HS, Fisher ME, Lin Y, et al. Neural evidence for enhanced
attention to mistakes among school-aged children with a
growth mindset. Dev Cogn Neurosci. 2017;24:42–50.
23. Mangels JA, Butterfield B, Lamb J, et al. Why do beliefs about
intelligence influence learning success? A social cognitive
neuroscience model. Soc Cogn Affect Neurosci. 2006;1:75–86.
24. Moser JS, Schroder HS, Heeter C, et al. Mind your errors: evidence
for a neural mechanism linking growth mind-set to adaptive post
error adjustments. Psychol Sci. 2011;22:1484–1489.
25. Yeager DS, Hanselman P, Walton GM, et al. A national experiment
reveals where a growth mindset improves achievement. Nature.
e108 Maternal Stress, Early Neurodevelopment, and Growth Mindset Journal of Developmental & Behavioral Pediatrics
26. Paunesku D, Walton GM, Romero C, et al. Mind-set interventions
are a scalable treatment for academic underachievement. Psychol
27. Andersen SC, Nielsen HS. Reading intervention with a
growth mindset approach improves children’s skills. Proc Natl
Acad Sci U S A. 2016;113:12111–12113.
28. Rowe ML, Leech KA. A parent intervention with a growth mindset
approach improves children’s early gesture and vocabulary
development. Dev Sci. 2019;22:e12792.
29. Pierce LJ, Thompson BL, Gharib A, et al. Association of perceived
maternal stress during the perinatal period with
electroencephalography patterns in 2-month-old infants. JAMA
30. van der Velde B, Junge C. Limiting data loss in infant EEG: putting
hunches to the test. Dev Cogn Neurosci. 2020;45:100809.
31. Cohen S, Kamarck T, Mermelstein R. A global measure of perceived
stress. J Health Soc Behav. 1983;24:385–396.
32. Dweck CS. Self-theories: Their Role in Motivation, Personality,
and Development. Psychology Press; 2000.
33. Saby JN, Marshall PJ. The utility of EEG band power analysis in the study
of infancy and early childhood. Dev Neuropsychol. 2012;37:253–273.
34. Anderson AJ, Perone S. Developmental change in the resting state
electroencephalogram: insights into cognition and the brain. Brain
35. Rivarola JE. [Volvulus of the small intestine]. Article. Bol Trab Acad
Argent Cir. 1951;35:165–167. A proposito del volvulus del intestino
36. Gabard-Durnam LJ, Mendez Leal AS, Wilkinson CL, et al. The
Harvard Automated Processing Pipeline for
Electroencephalography (HAPPE): standardized processing
software for developmental and high-artifact data. Front Neurosci.
37. Delorme A, Makeig S. EEGLAB: an open source toolbox for analysis
of single-trial EEG dynamics including independent component
analysis. J Neurosci Methods. 2004;134:9–21.
38. StataCorp. Stata Statistical Software: Release 16; 2019.
39. Preacher KJ, Curran PJ, Bauer DJ. Computational tools for probing
interactions in multiple linear regression, multilevel modeling, and
latent curve analysis. J Educ Behav Stat. 2016;31:437–448.
40. Gunderson EA, Gripshover SJ, Romero C, et al. Parent praise to 1- to
3-year-olds predicts children’s motivational frameworks 5 years
later. Child Dev. 2013;84:1526–1541.
Vol. 43, No. 2, February/March 2022 Copyright Ó2021 Wolters Kluwer Health, Inc. All rights reserved. e109