Content uploaded by Alexia Jolicoeur-Martineau
Author content
All content in this area was uploaded by Alexia Jolicoeur-Martineau on Dec 08, 2020
Content may be subject to copyright.
Downloaded from http://journals.lww.com/co-psychiatry by BhDMf5ePHKav1zEoum1tQfN4a+kJLhEZgbsIHo4XMi0hCywCX1AWnYQp/IlQrHD3i3D0OdRyi7TvSFl4Cf3VC4/OAVpDDa8K2+Ya6H515kE= on 12/08/2020
Downloadedfromhttp://journals.lww.com/co-psychiatry by BhDMf5ePHKav1zEoum1tQfN4a+kJLhEZgbsIHo4XMi0hCywCX1AWnYQp/IlQrHD3i3D0OdRyi7TvSFl4Cf3VC4/OAVpDDa8K2+Ya6H515kE= on 12/08/2020
Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved.
C
URRENT
O
PINION
Measuring resilience in children: a review of recent
literature and recommendations for future research
Leonora King
a
, Alexia Jolicoeur-Martineau
b
, David P. Laplante
c
,
Eszter Szekely
a
, Robert Levitan
d
, and Ashley Wazana
a
Purpose of review
Understanding variability in developmental outcomes following exposure to early life adversity (ELA) has
been an area of increasing interest in psychiatry, as resilient outcomes are just as prevalent as negative
ones. However, resilient individuals are understudied in most cohorts and even when studied, resilience is
typically defined as an absence of psychopathology. This review examines current approaches to resilience
and proposes more comprehensive and objective ways of defining resilience.
Recent findings
Of the 36 studies reviewed, the most commonly used measure was the Strengths and Difficulties
Questionnaire (n¼6), followed by the Child Behavior Checklist (n¼5), the Resilience Scale for Chinese
Adolescents (n¼5), the Rosenberg Self-Esteem Scale (n¼4), and the Child and Youth Resilience Scale
(n¼3).
Summary
This review reveals that studies tend to rely on self-report methods to capture resilience which poses some
challenges. We propose a complementary measure of child resilience that relies on more proactive
behavioral and observational indicators; some of our preliminary findings are presented. Additionally,
concerns about the way ELA is characterized as well as the influence of genetics on resilient outcomes
prompts further considerations about how to proceed with resiliency research.
Keywords
challenging puzzle task, children, early life adversity, resilience, gene-by-environment interactions
INTRODUCTION
Development is marked by periods of heightened
neural plasticity in which brain regions involved in
the regulation of emotion and stress are particularly
sensitive to the effects of early life adversity (ELA).
Although ELA can have long-term negative impacts
on the developing child, sometimes resulting in
psychiatric and behavioral problems [1 –4], many
children remain unaffected [5,6]. In fact, as many as
50% of individuals who are exposed to stressful
events do not go on to develop a stress-related
psychiatric illness in later life [6,7]. This suggests
that there are important variations in how people
respond to stress and traumatic events, with some
individuals prone to maladaptive outcomes and
others who function well. As a result, the focus of
recent research has been to better understand the
factors that contribute to positive outcomes in addi-
tion to negative ones.
Positive adaptation or better-than-expected out-
comes in the context of ELA is known as resilience
[8,9]. Although there are varying definitions of resil-
ience, it is best understood as a dynamic process that
integrates many systems within an individual as
well as in the environment of the individual, leading
to positive adaptation in the face of adversity. More
specifically, resilience is not a static state or trait-like
attribute [10], rather it is a biopsychosocial process
that involves several interacting factors including
a
Jewish General Hospital, Lady Davis Institute for Medical Research
and McGill University,
b
Mila, Jewish General Hospital, University of
Montreal,
c
Jewish General Hospital, Lady Davis Institute for Medical
Research, Montreal and
d
Family Mental Health Research Institute,
Centre for Addiction and Mental Health, University of Toronto, Toronto,
Canada
Correspondence to Ashley Wazana, MD, Child Center for Development
and Mental Health, Jewish General Hospital, 4335 Chemin Cote Sainte-
Catherine West, Montre´al, QC, Canada H3T 1E4.
Tel: +1 514 340 8222x27652; e-mail: ashley.wazana@mcgill.ca
Curr Opin Psychiatry 2021, 34:10– 21
DOI:10.1097/YCO.0000000000000663
www.co-psychiatry.com Volume 34 Number 1 January 2021
REVIEW
Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved.
neurobiological mechanisms, stress and emotional
regulation systems, prosocial skills, coping strategies
and temperament [11–14].
MEASURING RESILIENCE IN CHILDREN
How resilience is characterized and detected may
vary depending on the developmental period as
responses to challenges are typically content and
context-specific [15]. It has been suggested that
detecting resilient functioning in young children
may be more reliable given that their vulnerability
confers increased sensitivity to the environment
making them more responsive to the task at hand
[16]. Still, the methods by which resilience is cap-
tured and measured (whether in children or adults)
poses some challenges particularly because resil-
ience has often been characterized as an absence
of psychopathology or dysfunction although the
two are not synonymous. Rather, resiliency research
is more robust when it captures some of the more
proactive cognitive, emotional, and behavioral pro-
cesses associated with resilient functioning.
The current review aims to highlight recent
trends in resiliency research by reviewing studies
of child resilience published in the last 18 months.
Using PubMed, a biomedical literature database, the
following search parameters were entered: ((((resil-
ience[Title] OR resilient[Title] OR resiliency[Title]
OR ‘positive outcomes’[Title] AND ((’2019/04/
15’[Date - Publication]: ‘2020’[Date - Publication])))
AND (child[Title] OR children[Title]) AND (english[-
Filter])) NOT (review[Title/Abstract]). A total of 99
articles were returned. After scanning titles and
abstracts for relevance, 34 studies were excluded
for the following reasons: they were measuring resil-
ience in parents, caregivers or mothers who had
children with some disability, disorder or medical
condition (n¼34), whereas the remaining studies
were excluded (n¼29) because they were deemed
irrelevant for other reasons (e.g., were editorials,
consisted of retrospective reports of ELA or the name
of the cohort had the term resilience in it). The final
selection consisted of 36 articles for which the age
range was birth to 19 years old.
The majority of the studies identified in the
review used quantitative approaches, whereas four
studies used qualitative methods [17 –20] and three
studies incorporated a mixed-methods research
design [21–23]. Twenty-four of the 36 studies
reviewed were cross-sectional, seven were longitu-
dinal and the remaining five were intervention-
based. Although measures of psychopathology were
featured in the reviewed studies, unless they were
used to construct a measure of resilience, they are
not reported here as it was not the purpose of the
review. Otherwise, resilience was featured as the
outcome measure in 27 studies, whereas another
seven studies examined resilience as a mediating
factor (n¼4) [24,25
&
,26,27] or as a predictor variable
(n¼3) [21,28,29] and two studies assessed the psy-
chometric properties of resilient measures [30,31].
In terms of sample size, the range of participants for
the qualitative studies was from nine to 137,
whereas for quantitative studies, the range was from
24 to 51 156 participants. The majority of measures
were based on child or youth self-reports (n¼26),
whereas nine of the 36 studies were based on parent-
reports and one on teacher reports (Table 1).
The most common instrument used to measure
resilience in children was the Strengths and Diffi-
culties Questionnaire (SDQ) which was used in six of
36 studies. The SDQ captures both positive and
negative outcomes in children and can be adminis-
tered to children, parents, or teachers. The 25-item
SDQ (and an optional incapacity section) measures
current attention/hyperactivity problems, conduct
problems, emotional problems, peer relationships,
and prosocial behaviors [32]. In the current review,
three of the six studies administered the parent-
reported version of the SDQ [22,33,34], whereas
the child-reported version was used twice [35,36]
and the teacher-reported version once [37]. Of these,
three studies included SDQ total scores in their
analyses [22,35,37], two studies used both total
scores and the prosocial skills subscale [33,34] and
one study used only the peer relations subscale of
the SDQ [36].
The other two most common measures of child
resilience were the Resilience Scale for Chinese Ado-
lescents (RSCA) and the Child Behavior Checklist
(CBCL), each of which were administered in 5 stud-
ies. The RSCA is a 27-item survey with a 5-point
KEY POINTS
Measures of resilience in children are moving away
from defining resilience as an absence
of psychopathology.
The majority of child resiliency measures tend to be
based on self-reports and to a lesser extent,
parent reports.
A more objective and comprehensive measure of child
resilience that combines self-ratings and interrater
codings of video observations in response to a
challenging task is proposed.
Considerations about the ways in which ELA is
characterized as well as the influence of genetics on
resilient outcomes are discussed.
Measuring resilience in children King et al.
0951-7367 Copyright ß2020 Wolters Kluwer Health, Inc. All rights reserved. www.co-psychiatry.com 11
Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved.
Table 1. Review of studies and measures used
Study
Age range
(in years)
Informant Sample
size
Study
design
Resilience
variable
Rosenberg
self-esteem CYRM CBCL Qualitative Other measure(s)
Asante et al., 2019 Mean age¼14 Child 16 Cross-sectional Outcome x Qualitative semistructured interviews
Beeckman et al., 2019 8– 18 Child 59 Cross-sectional Mediator AFQ-Y þCPAQ-A
Bethell et al., 2019 6– 17 Parent 51,156 Cross-sectional Outcome Child Flourishing Index, Family Resilience &
Connection Index and Social Engagement Index
(constructed using items from the NSCH)
Cheetham-Blake
et al., 2019
7– 11 Child 34 Cross-sectional Predictor x The Kidcope questionnaireþat-home parent –child
dyadic interviews
Cohen et al., 2019 10– 11 Child 167 Cross-sectional Predictor x My Life Today scale þ10-item emotional regulation
scale þThe BSI
Conover et al., 2020 6– 10 Parent 36 Intervention Outcome x x Context of ‘Tell Me a Story’ intervention; Ego-
Resiliency Q-Sort (ER-11); total CBCL as well as
internalizing and externalizing subscales used
Cui et al., 2020 14– 18 Child 1354 Longitudinal Outcome x x Future Events Questionnaire; child maltreatment was
measured every two years from birth onwards
Ellersgaard et al., 2020 7 Child 522 Cross-sectional Outcome KIDSCREEN-27 (Quality of life measures) & Self-
esteem scale ‘I think I am’
Elmore et al., 2020 8– 17 Parent 40 302 Cross-sectional Mediator Using the ‘HOPE: Health Outcomes from Positive
Experiences’ framework, the following factors were
constructed: emotional competency, constructive
social engagement, safe and stable environment,
trusting relationships with adults
Study
Age range
(in years) Informant
Sample
size
Study
design
Resilience
variable SDQ
Rosenberg
self-esteem CYRM CD-RISC Qualitative Other measure(s)
Fogarty
et al., 2019
10 Parent 9 Longitudinal Outcome x x Semistructured interviews about: experiences of abuse
within relationships, making decisions around
staying or leaving relationships, parenting, how
they and their children coped, and help seeking
Folayan
et al., 2020
6– 16 Child 1001 Cross-sectional Psycho-metrics x x Perceived Social Support scale
Hebbani
et al., 2020
Mean age
¼19.7
Child 331 Cross-sectional Outcome x Socio-cultural factors Questionnaire (culturally
mediated factors linked to resilience) þSGSS þthe
Ryff and Keyes Scales of Psychological Well Being
Herbell et al.,
2020
6– 17 Child 1900 Cross-sectional Outcome Child Flourishment Index þFamily Resilience and
Connection Index; parental coping and parental
emotional support were also measured (constructed
using items from the NSCH)
Jefferies et al.,
2019
9– 12 Child 227 Cross-sectional Outcome x x Other measures of physical activity and competence
including PLAYfun, PLAYself, PLAYinventory,
PLAYparent and PLAYpe_teacher; also the peer
relations subscale of the SDQ was used
Kaiser et al., 2020 13– 14 Child 12 Cross-sectional Outcome x Phenomenological qualitative approach using in-depth
interviews
Mood and anxiety disorders
12 www.co-psychiatry.com Volume 34 Number 1 January 2021
Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved.
Table 1 (Continued )
Study
Age range
(in years) Informant
Sample
size
Study
design
Resilience
variable SDQ
Rosenberg
self-esteem CYRM CD-RISC Qualitative Other measure(s)
Kirby et al., 2020 4 –5 Teacher 636 Longitudinal Outcome x GHQ-28, Kessler-6, Infant Characteristics
Questionnaire, FRS adult deprivation questions,
EYFSP, maternal self-efficacy; these measures were
administered either at 6, 18, 12, or 24 months in
parents
Study Age range
(in years) Informant
Sample
size
Study
design
Resilience
variable
SDQ
RSCA CYRM CBCL Qualitative Other measure(s)
Liu et al., 2020 12–14 Child 646 Cross-sectional Outcome x Also measured parent-child relations
Llistosella et al., 2019 12– 19 Child 270 þ15 þ432 Cross-sectional Psychometrics x Study I ¼CRYM-28; Study II ¼semi-structured
interviews with 6 youth aged 17 to 19, 4
participants from Study I and 5 resilient experts;
Study III ¼validation of the CYRM-32; convergent
and discriminant validity was compared with the
BRCS, ACS, and AF5
Malee et al., 2019 6 –14 Parent 448 Longitudinal Outcome x Completed every 6 months; resilience was defined as
having CBCL T-scores within the normal range (T-
score <60)
Mantovani et al.,
2020
14– 18 Child 9 Intervention Outcome x Semistructured, one-to-one interviews in relation to a 1-
year peer-mentoring relationship
Matsuyama et al.,
2020
6– 10 Parent 2712 Longitudinal Mediator CRCS; resilience as a mediator between parent –child
interactions and dental caries incidence
Mayr et al., 2020 9– 15 Child 24 Intervention Outcome Lifestyle intervention; cardiorespiratory fitness and
Piers-Harris 2 children’s self-concept scale was
assessed at baseline and at 12 weeks
Miller-Graff
et al., 2020
4– 17 Parent 385 Cross-sectional Outcome x SDQ ¼Total and prosocial skills subscale; other
parental measures included: the FACES-IV, the PBS,
and the RRC-ARM
Morgan
et al., 2020
9– 16 Child 252 Cross-sectional Outcome x Also administered the Perceived Parental Rearing
Patterns Scale (EMBU), Chinese version
Study
Age range
(in years) Informant
Sample
size
Study
design
Resilience
variable SDQ RSCA
Rosenberg
self-esteem CBCL Qualitative Other measure(s)
Ndetei et al., 2019 11– 18 Child 1883 Cross-sectional Outcome x Resilience scale (ER-89) þYSR
Rotheram-Borus
et al., 2019
0– 5 Parent 1073 Longitudinal Outcome x x Resilience was defined as being within the normal
range for growth, cognitive functioning, and
behavior; measures include: the Bayley Scale of
Infant Development, the Peabody Picture
Vocabulary Test, the KABC
Shaw et al., 2019 11, 13, 15 Child 5286 Cross-sectional Outcome 5-item World Health Organization Wellbeing
index þ3 promotive factors: frequency of eating
family meals together, classmate support and
teacher support
Tam et al., 2020 9 –10 Child 276 Intervention Outcome x x Resilience-based intervention; also administered:
MSAS and the CSES-A
Measuring resilience in children King et al.
0951-7367 Copyright ß2020 Wolters Kluwer Health, Inc. All rights reserved. www.co-psychiatry.com 13
Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved.
Table 1 (Continued )
Study
Age range
(in years) Informant
Sample
size
Study
design
Resilience
variable SDQ RSCA
Rosenberg
self-esteem CBCL Qualitative Other measure(s)
Tian et al., 2019 10–17 Child 2898 Cross-sectional Predictor x Also assessed self-harm and depressive symptoms
Veronese et al.,
2020
7– 13 Child 29 Cross-sectional Outcome x Participatory approach based on children’s drawings
of maps representing safe and unsafe places
followed by a guided walk (n¼10) through those
places
Vreeman et al.,
2019
10– 14 Child 253 Intervention Outcome x Context of RCT; depression symptoms were measured
using the Patient Health Questionnaire (PHQ-9);
resilience was defined as having low scores on
SDQ Total and PHQ-9
Wang et al., 2019 0.5 –6 Parent 2397 Cross-sectional Mediator DECA þInfant-Junior Middle School Student’s Ability of
Social Life Scale; having a score of 60 or more on
DECA was defined as resilience
Worku et al., 2019 13 Child 137 Cross-sectional Outcome x Conducted interviews and focus groups þthe Ryff and
Keyes Scales of Psychological Well Being
Study Age range (in years) Informant Sample size Study design Resilience variable Other measure(s)
Wu et al., 2020 8–14 Child 816 Longitudinal Outcome Self-rating Scale of Psychological Resilience; the
preliminary questionnaire was validated in a
presample of 269 children
Xiao et al., 2019 10– 17 Child 2898 Cross-sectional Outcome RSCA ¼Resilience Scale for Chinese Adolescents
Young et al., 2020 4 Child 64 Longitudinal Outcome Different types of intelligence were assessed using the
WPPSI-III; language ability was determined using
the CELF-Pre2; visual ability and motor coordination
was assessed using the Beery-Buktenica Test of VMI;
cortical thickness, surface area and brain volume
were assessed using MRI scans; resilient was
defined as having good neurodevelopmental
outcomes and cognitive abilities
ACS, Coping Strategies for Adolescents; AF5, Self-Concept Form 5; AFQ-Y, Avoidance and Fusion Questionnaire for Youth; BRCS, Brief Resilient Coping Scale; BSI, Brief Symptom Inventory; CBCL, Child Behavior
Checklist; CD-RISC, Connor Davidson-Resilience Scale; CELF-Pre2, Clinical Evaluation of Language Fundamentals—Preschool, 2nd Ed; CPAQ-A, Chronic Pain Acceptance Questionnaire –Adolescent version; CRCS,
Children’s Resilient Coping Scale; CSES-A, Cultural Self-Efficacy Scale for Children and Adolescents; CYRM, Child and Youth Resilience Measure; DECA, Devereux Early Childhood Assessment; EMBU, Egna Minnen av
barndoms uppfostran; EYFSP, Early Years Foundation Stage Profile; FACES-IV, Family Adaptability and Cohesion Scale; FRS, Family Resources Survey; GHQ-28, General Health Questionnaire; KABC, Kaufman
Assessment Battery for Children; MSAS, Making Sense of Adversity Scale; NSCH, National Survey of Children’s Health; PBS, Parent Behavior Scale; RRC-ARM, Resilience Research Centre-Adult Resilience Measure;
RSCA, Resilience Scale for Chinese Adolescents; SDQ, Strengths and Difficulties Questionnaire; SGSS, Sherer General self-efficacy scale; VMI, visual motor integration; WPPSI-III, Wechsler Preschool and Primary Scales
of Intelligence 3rd Ed; YSR, Youth Self Report.
Mood and anxiety disorders
14 www.co-psychiatry.com Volume 34 Number 1 January 2021
Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved.
Likert scale that taps into seven domains: goal focus,
emotion control, positive cognition, family support,
interpersonal assistance, personal strength, and sup-
port [38]. The RSCA was exclusively used in studies
with Chinese participants [29,39,40
&
,41,42]. The
CBCL addresses a range of emotional and behavioral
problems including internalizing and externalizing
symptoms, attention problems, and aggressive
behaviors; total scores or its subscales can be used
[43]. The preschool version of the CBCL contains
100 items, is intended for children aged 1.5 –5 years
and relies on parent reports. The school-age version
is made up of 118 items, is designed for children
aged 6–18 years and can be teacher or parent-
reported; otherwise if the child is 11 years or older,
then the 112-item Youth Self-Report (YSR) version
of the CBCL can be used [44]. For the current review,
three studies relied on parent reports [34,45,46
&
],
whereas two studies administered the YSR version
[47
&
,48]. Of the studies identified in the current
review, one study examined the CBCL total scores
as well as the internalizing and externalizing sub-
scales [46
&
], another analyzed the CBCL total scores
along with the aggressive subscale [34], another used
the activities and social subscale [47
&
], and two used
the CBCL total scores only [45,48]. However, in two
of these studies, the CBCL scores were used as an
indicator of behavioral and emotional problems
rather than resilience [46
&
,48]. The other studies
used the CBCL ‘activities and social’ subscale as a
measure of social competence [47
&
], whereas the
remaining two studies defined resilience as having
CBCL scores in the normal range [34,45].
The next most commonly used instruments
were the Rosenberg Self-Esteem Scale and the Child
and Youth Resilience Measure (CYRM). The Rosen-
berg Self-Esteem Scale was administered in four
studies [28,30,40
&
,47
&
] and the CYRM in three
[31,36,46
&
]. The Rosenberg Self-Esteem scale is com-
posed of 10 items and conforms to a 4-point Likert
scale [49]. There are three versions of the CYRM, the
12, 28, and 32-item versions all of which are based
on a 5-point Likert scale [50,51]. The CYRM-12 was
administered in two studies [36,46
&
] whereas the
CYRM-32 was used and validated in one study [31].
Another two studies [30,52] administered the
25-item Connor Davidson-Resilience Scale [53],
although Folayan et al. [30] utilized the reduced
10-item version [54]. The Ryff and Keyes Scales of
Psychological Well Being is an instrument consist-
ing of six subscales: self-acceptance, positive rela-
tions with others, autonomy, environmental
mastery, purpose in life and personal growth [55]
and was administered in two studies as well [23,52].
The remaining studies used other measures of resil-
ience and are indicated in Table 1.
With the exception of six studies where resilience
was either characterized as an absence of psychologi-
cal inflexibility [24], having low scores on the SDQ
[35,37], or being in the normal range behaviorally
(e.g., CBCL scores) [34,45], developmentally [34], or
cognitively [56], the remaining studies used actual
resilient scales or measures of positive adjustment
rather than relying on an absence of psychopathol-
ogy to characterize resilience. This is reassuring con-
sidering that a similar review which was conducted
recently (from 2004 to 2018) and examined measures
of resilience in children, found that over half of the
identified studies characterized resilience as an
absence of psychopathology, namely low levels of
externalizing and internalizing problems, anxiety,
depressive symptoms, aggression, delinquency, anti-
social behavior, and drug use [57
&&
]. It is possible that
current research in psychiatry is starting to address
concerns about equating an absence of psychopa-
thology with resilience.
A significant limitation of the studies identified
in the current review and of those reviewed by Gart-
land et al. [57
&&
] is that none featured observable
behavioral measures of resiliency in the children;
rather they were all based on self-reports and par-
ent-reports or to a lesser extent, teacher-reports. Some
of the limitations of relying on self-report measures
are that they introduce social-desirability and recall
biases [58] and disagreement among informants has
been a long-standing issue in research [59,60]. Obser-
vational measures of resilience such as how a child
copes with a stressful task may be a more reliable
means of detecting resilience in young children as it
provides insight into the behavioral and cognitive
processes involved. Although there was one study
identified in our review which used the BEST-C (the
children’s version of the Trier Social Stress Test) and
includes verbal reports assessing self-reported stress
and coping in response to the task, these reports were
only examined in the context of a manipulation
check. Furthermore, the main purpose of this study
was to assess the impact of this task on salivary
cortisol and heart rate [21]. An alternative to this
paradigm is the Challenging Puzzles Task (CPT),
which not only captures how children deal with a
stressful task but also taps into three indicators of
resilience: positive self-evaluation, hopefulness, and
motivation [15,61–63]. These constructs are detect-
able in children as young as four years old [64] and are
relatively stable up to five years later [65].
RECOMMENDATIONS FOR FUTURE
RESEARCH
The Maternal Adversity, Vulnerability and Neurode-
velopment (MAVAN) project, a community-based,
Measuring resilience in children King et al.
0951-7367 Copyright ß2020 Wolters Kluwer Health, Inc. All rights reserved. www.co-psychiatry.com 15
Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved.
prospective cohort study of pregnant mothers and
their offspring, is currently using the CPT to identify
the developmental pathways associated with risk and
resilience. Dyads are assessed longitudinally, with
multiple assessments of both mother and child in
home and laboratory from pregnancy to late adoles-
cence. In our study, the CPT was administered to five-
year-old children by a trained experimenter in the
child’s home alongside other measures of child
behavior. The CPT [66] is a modified version of the
task used by Cole et al. [64,65] with children of the
same age: our adapted version consisted of five puzzle
trials instead of the original seven trials. The CPT
consists of a series of possible and impossible puzzles,
whereby reactions to a challenge (in this case, three
impossible puzzles) are captured via a rating scale.
Puzzles one and five are possible to solve and can be
completed with the help of the research assistant as
needed whereas puzzles 2–4 are impossible and have
a time limit of 2minutes. A picture of each puzzle is
shown before the challenge begins and after each
puzzle the children are asked the following questions:
How well do you think you did on the puzzle? (posi-
tive self-evaluation); How do you think you will do on
the next puzzle?(hopefulness); How do you feel about
doing the next puzzle? (motivation). To answer these
questions, a prepuzzle trial is conducted to ensure the
child understands the accompanying rating scales (of
stars and happy/sad faces) which range from 1 (nega-
tive outlook) to 5 (positive outlook; Fig. 1).
Measures of resilience were captured in two
ways. First, self-ratings according to the above ques-
tions were recorded and used to conduct data-driven
trajectory analyses across the five puzzles for each
indicator of resilience. Whether assessing positive
self-evaluation, hopefulness or motivation, prelimi-
nary data corresponding to these trajectory analyses
revealed three distinct and consistent response pat-
terns. One group of children remained relatively
stable and exhibited positive self-appraisal through-
out the puzzle task even when faced with failures
(resilient group), another group showed a decrease
in self-appraisal when faced with impossible puzzles
followed by an improvement in self-appraisal when
presented with a solvable puzzle (rebound group),
whereas a third group of children exhibited steadily
decreasing self-appraisal even when presented with
a solvable puzzle post-impossible trials (discouraged
group; Fig. 2). Similar trajectories have been
detected in other studies on resilience [67 –69], fur-
ther validating our findings.
Second, a video component of the CPT is cur-
rently being coded according to the Disruptive
Behavior Diagnostic Observation Schedule (DB-
DOS), a structured clinic-based assessment designed
to capture emotional dysregulation in young
children [70,71]. For our purposes, the DB-DOS was
adapted to capture salient behaviors relevant to the
CPT: anger modulation, stress reactivity, compe-
tence, prosocial skills, and coping strategies. Exam-
ples of the behaviors in question are noted across all
five puzzles with attention paid to the intensity and
frequency as well as the child’s verbal and physical
cues (e.g., frowning, self-talk, complaints, shrugging
of shoulders, crossing of arms). Codes range from 0
to 3 with 3 indicating that the behavior in question
is present to a high degree and 0 indicating that the
behavior is not present. The scores are then totaled
across each domain. Because of the subjectivity in
coding, internal reliability was set at 80% with the
second coder needing to demonstrate agreeableness
on 4/5 behavior codes before going on to code inde-
pendently. Additionally, 40% of the videos were
double-coded and 25% triple-coded to establish
interrater reliability. Essentially, this video compo-
nent of the CPT will complement the self-ratings with
observed measures, thereby enriching this task as a
robust and valid measure of resilience. Analyses using
this measure are currently underway.
EARLY LIFE ADVERSITY
Models of resilience have historically included con-
sideration of developmental pathways including the
role of ELA and constitutional (e.g., genetic) suscep-
tibility. The operationalization of ELA requires spe-
cific attention as one factor that is often overlooked
and difficult to disentangle is the timing of exposure
to ELA. The early life period is critical as some win-
dows of development may be more influential than
others. For example, the prenatal period has been the
focus of much investigation because the fetus is
forming according to incoming signals from the
maternal environment [72]. The fetus is therefore
susceptible to prenatal stress and maternal mood
states whose effects can be directly transmitted via
neuroendocrine signals and epigenetic programming
[73,74]. On the other hand, postnatal influences have
the potential to modulate or even override prenatal
effects as well as genetic vulnerability effects [75– 77].
Children’s brains are known to be extremely plastic
up until early adulthood [78,79] and compelling
evidence from attachment and maternal care
research demonstrates the profound impact of post-
natal influences on child development [80– 82].
Other research suggests that it is not necessarily a
question of timing, but whether the prenatal envi-
ronment ‘matches’ the postnatal environment, a
concept known as the match-mismatch hypothesis
[83]. If the postnatal environment is congruent with
the prenatal environment, the fetus’ adaptations in
utero will apply outside the womb resulting in more
Mood and anxiety disorders
16 www.co-psychiatry.com Volume 34 Number 1 January 2021
Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved.
favorable outcomes. However, if the prenatal and
postnatal environments are a mismatch, the fetus
will be maladapted to the postnatal environment,
leading to negative outcomes. Another theory pro-
poses that prenatal stress can promote postnatal
plasticity and positive outcomes (if reared in a sup-
portive environment) because of an increased sensi-
tivity that develops from prenatal stress exposure
[84]. Regardless of timing effects, perhaps the more
important question is: does prenatal ELA extend into
FIGURE 1. Images and examples of the Challenging Puzzles Task (CPT). Three questions corresponding to positive self-evaluation,
hopefulness and motivation are asked after each puzzle and participants can respond using the child-friendly rating scales.
Measuring resilience in children King et al.
0951-7367 Copyright ß2020 Wolters Kluwer Health, Inc. All rights reserved. www.co-psychiatry.com 17
Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved.
the postnatal period and if so, how chronic and/or
severe is the ELA? To answer this question, longitudi-
nal measures of ELA are necessary. However, the
chronicity and severity of ELA is not often captured
when assessing environmental risk; rather the mere
presence or absence of a stressor is captured [13,85,86].
Categorizing environmental risk this way likely leads
to inconsistent results as one incident of child mal-
treatment can have a very different impact compared
with having experienced years of child maltreatment.
THE ROLE OF GENETICS
No article identified for this review assessed the
influence of genetics on resilient outcomes in
children although several gene variants (namely,
those associated with the serotonin transporter,
BDNF, CRHR1, and DRD4 [BDNF ¼brain-derived
neurotrophic factor, CRHR1 ¼corticotropin-releas-
ing hormone receptor 1, DRD4 ¼dopamine receptor
4]) have been associated with resilience because of
their implication in emotional and stress regulation
[12,87–93]. Despite a general consensus that there
are direct genetic influences on resilience, mixed
results from genetic studies [94
&&
,95
&
,96] have
prompted a reflection about how to capture the
complexity of genetic susceptibility and its interac-
tion with environmental factors. As a result, current
research efforts are not only moving away from
candidate gene studies, but they are also moving
FIGURE 2. Trajectory patterns for the three indicators of resilience on the Challenging Puzzle Task (CPT) identifying children
as being in the resilient, rebound or discouraged group.
Mood and anxiety disorders
18 www.co-psychiatry.com Volume 34 Number 1 January 2021
Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved.
toward gene-by-environment (G E) interaction
studies to explain behavior. Emerging evidence sug-
gests that a combination of environmental and
genetic factors likely influence the relationship
between stress exposure and resilient outcomes. In
other words, genotype may only be a risk factor
under certain environmental conditions [7], a con-
cept that is supported by the differential suscepti-
bility hypothesis [83]. Specifically, the differential
susceptibility hypothesis posits that an underlying
biological vulnerability may not only render indi-
viduals more sensitive to adverse environments
(resulting in worse outcomes), but equally sensitive
to positive environments as well, flourishing as a
result [96]. On the other hand, individuals without
genetic susceptibility may be more likely to perse-
vere regardless of environmental quality.
GE approaches are consistent with findings in
molecular biology which reveal that gene expres-
sion is contingent upon transcriptional signals that
derive from the internal and the external environ-
ment. That the majority of G E studies demon-
strate moderate replicability [97], leads to reflection
about a number of factors. First, most G E studies
focus on a restricted range of environmental factors
and a limited number of genes. This suggests the
need for approaches that can model complex and
comprehensive lists of environmental and genetic
factors [98]. Second, most G E studies are based on
a diathesis-stress model whereby genetic suscepti-
bility to psychiatric disorders manifests under
stressful conditions with more severe stressors
increasing the chances that a disorder will develop
in a dose-dependent manner [99]. The concern is
that the diathesis-stress model often focuses on
negative environmental influences and negative
outcomes; otherwise an absence of adversity and
dysfunction is measured in place of positive factors
[8,13]. Measuring resilience as the absence of adver-
sity or dysfunction may mask potential differential
susceptibility findings as such approaches favor
vulnerability explanations [100] which may lead
to inconsistent results. The diathesis-stress model
also fails to explain why susceptibility genotypes
have not been selected against over the course of
evolution. The significant frequency of many of
these ‘susceptibility’ genotypes [95
&
] suggest some
advantage to carrying ‘risk alleles’ or at the very
least, that the expression of such genes depends on
variability in the environment.
CONCLUSION
The results from this review suggest that research on
resilience in children is moving away from opera-
tionalizing resilience merely as the absence of
psychopathology, in favor of an understanding that
resilience is a dynamic process that encompasses
several interacting features including coping strate-
gies, emotional regulation abilities, flexibility, self-
esteem, a positive outlook, and prosocial skills.
Some of the studies identified in this review
attempted to capture some of this complexity by
using mixed-methods approaches or by using mul-
tiple instruments to measure resilient functioning.
Also important to note is that although the majority
of the reviewed studies featured resilience as an
outcome variable, very few reported an effect size
[23,33,36,37,101], a key measure needed to deter-
mine the explanatory value of the models being
tested. Despite the move toward more valid mea-
sures of resilience, the exclusive reliance on self-
report or parent-report measures poses some chal-
lenges as resilience is a multidimensional construct
that relies on behavioural and cognitive processes.
For this reason, we propose a method of operation-
alizing resilience in young children that combines
behavioral tasks, self-ratings, and observational
measures. Preliminary findings derived from this
approach appear promising.
We also highlight other considerations in resil-
ience research and propose recommendations for
going forward pertaining to: how ELA is character-
ized; and the influence of genetics on resilient out-
comes. Having a better understanding of these
factors may help explain variability in outcomes.
Although this review outlines measures of resilience
in children, one of the next steps should be the
construction and validation of resilience measures
applicable across the lifespan. This would enable the
exploration of the stability of resilient functioning,
critical protective factors, including key strategies
and processes that could be used in the promotion of
mental wellness. The application of such interven-
tion strategies would be most optimal in early child-
hood when the plasticity of children’s behavior,
cognitive and emotional development can be
exploited to undo maladaptive patterns not
yet entrenched.
Acknowledgements
We would like to thank all the families who participated
in this study, without which this research would not have
been possible.
Financial support and sponsorship
The primary sources of funding for this study include the
Canadian Institute for Health Research (CIHR), grant
numbers: 359912, 365309, and 231614.
Conflicts of interest
There are no conflicts of interest.
Measuring resilience in children King et al.
0951-7367 Copyright ß2020 Wolters Kluwer Health, Inc. All rights reserved. www.co-psychiatry.com 19
Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved.
REFERENCES AND RECOMMENDED
READING
Papers of particular interest, published within the annual period of review, have
been highlighted as:
&of special interest
&& of outstanding interest
1. Babenko O, Kovalchuk I, Metz GA. Stress-induced perinatal and transge-
nerational epigenetic programming of brain development and mental health.
Neurosci Biobehav Rev 2015; 48C:70–91.
2. Murgatroyd C, Wu Y, Bockmuhl Y, et al. Genes learn from stress: how
infantile trauma programs us for depression. Epigenetics 2010; 5:194 –199.
3. Silberman DM, Acosta GB, Zorrilla Zubilete MA. Long-term effects of early
life stress exposure: role of epigenetic mechanisms. Pharmacol Res 2016;
109:64– 73.
4. Hornung OP, Heim CM. Gene-environment interactions and intermediate
phenotypes: early trauma and depression. Front Endocrinol (Lausanne)
2014; 5:14.
5. Peskin MZ. Chapter 4: Genetic process in resilience and vulnerability and the
consequence of abuse. In: Positive mental health, fighting stigma and
promoting resiliency for children and adolescents. London, UK: Elsevier;
2016.
6. Bonanno GA, Mancini AD. The human capacity to thrive in the face of
potential trauma. Pediatrics 2008; 121:369 –375.
7. Claessens SE, Daskalakis NP, van der Veen R, et al. Development of
individual differences in stress responsiveness: an overview of factors
mediating the outcome of early life experiences. Psychopharmacology (Berl)
2011; 214:141– 154.
8. Masten AS. Ordinary magic: resilience processes in development. Am
Psychol 2001; 56:227– 238.
9. Luthar SS, Sawyer JA, Brown PJ. Conceptual issues in studies of resilience:
past, present, and future research. Ann NY Acad Sci 2006; 1094:10 5–115.
10. Norris FH, Tracy M, Galea S. Looking for resilience: understanding the
longitudinal trajectories of responses to stress. Soc Sci Med 2009;
68:2190– 2198.
11. Masten AS. Resilience in developing systems: progress and promise as the
fourth wave rises. Dev Psychopathol 2007; 19:921 –930.
12. Agnafors S, Svedin CG, Oreland L, et al. A biopsychosocial approach to risk
and resilience on behavior in children followed from birth to age 12. Child
Psychiatry Hum Dev 2016; 48:584–596.
13. Reuben JD, Shaw DS. Resilience in the offspring of depressed mothers:
variation across risk, domains, and time. Clin Child Fam Psychol Rev 2015;
18:300– 327.
14. Davydov DM, Stewart R, Ritchie K, et al. Resilience and mental health. Clin
Psychol Rev 2010; 30:479– 495.
15. Fergus S, Zimmerman MA. Adolescent resilience: a framework for under-
standing healthy development in the face of risk. Annu Rev Public Health
2005; 26:399– 419.
16. Bonanno GA, Diminich ED. Annual research review: positive adjustment to
adversity–trajectories of minimal-impact resilience and emergent resilience. J
Child Psychol Psychiatry 2013; 54:378 –401.
17. Asante KO. Factors that promote resilience in homeless children and
adolescents in Ghana: a qualitative study. Behav Sci (Basel) 2019; 9:64.
18. Kaiser E, Sinanan AN. Survival and resilience of female street children
experiencing sexual violence in Bangladesh: a qualitative study. J Child
Sex Abus 2020; 29:550– 569.
19. Mantovani N, Gillard S, Mezey G, et al. Children and young people ‘in care’
participating in a peer-mentoring relationship: an exploration of resilience. J
Res Adolesc 2020; 30(Suppl. 2):380–390.
20. Veronese G, Sousa C, Cavazzoni F, et al. Spatial agency as a source of
resistance and resilience among Palestinian children living in Dheisheh
Refugee Camp, Palestine. Health Place 2020; 62:102304.
21. Cheetham-Blake TJ, Turner-Cobb JM, Family HE, et al. Resilience character-
istics and prior life stress determine anticipatory response to acute social
stress in children aged 7 –11 years. Br J Health Psychol 2019; 24:282 –297.
22. Fogarty A, Woolhouse H, Giallo R, et al. Promoting resilience and wellbeing
in children exposed to intimate partner violence: a qualitative study with
mothers. Child Abuse Negl 2019; 95:104039.
23. Worku BN, Urgessa D, Abeshu G. Psychosocial conditions and resilience
status of street children in Jimma Town. Ethiop J Health Sci 2019;
29:361– 368.
24. Beeckman M, Hughes S, Van Ryckeghem D, et al. Resilience factors in
children with juvenile idiopathic arthritis and their parents: the role of child
and parent psychological flexibility. Pain Med 2019; 20:1120 –1131.
25.
&
Elmore AL, Crouch E, Kabir Chowdhury MA. The interaction of adverse
childhood experiences and resiliency on the outcome of depression among
children and youth, 8– 17 year olds. Child Abuse Negl 2020; 107:104616.
This cross-sectional study examines adverse childhood experiences in addition to
positive ones. Data were drawn from the National Survey of Children’s Health for
which 40 302 parents of children aged 8– 17 years were surveyed. Indices of
emotional competency, social engagement, environment factors and relationships
with adults were constructed.
26. Matsuyama Y, Isumi A, Doi S, et al. Longitudinal analysis of child resilience
link to dental caries. Pediatr Dent 2020; 42:308 –315.
27. Wang L, Qu G, Tang X, et al. Child neglect and its association with social
living ability: does the resilience attenuate the association? Psychol Health
Med 2019; 24:519– 529.
28. Cohen E, Eshel Y, Kimhi S, et al. Individual resilience: a major protective
factor in peer bullying and victimization of elementary school children in Israel.
J Interpers Violence 2019; 1–20.
29. Tian X, Chang W, Meng Q, et al. Resilience and self-harm among left-behind
children in Yunnan, China: a community-based survey. BMC Public Health
2019; 19:1728.
30. Folayan MO, Oginni O, Arowolo O, et al. Internal consistency and correlation
of the adverse childhood experiences, bully victimization, self-esteem, resi-
lience, and social support scales in Nigerian children. BMC Research Notes
2020; 13:331.
31. Llistosella M, Gutie
´rrez-Rosado T, Rodrı
´guez-Rey R, et al. Adaptation and
psychometric properties of the Spanish version of Child and Youth Resi-
lience Measure (CYRM-32). Front Psychol 2019; 10:1410.
32. Goodman R. The Strengths and Difficulties Questionnaire: a research note. J
Child Psychol Psychiatry 1997; 38:581– 586.
33. Miller-Graff LE, Scheid CR, Guzma
´n DB, et al. Caregiver and family factors
promoting child resilience in at-risk families living in Lima, Peru. Child Abuse
Negl 2020; 108:104639.
34. Rotheram-Borus MJ, Christodoulou J, Hayati Rezvan P, et al. Maternal HIV
does not affect resiliency among uninfected/HIV exposed South African
children from birth to 5 years of age. Aids 2019; 33(Suppl. 1):S5–s16.
35. Vreeman RC, Nyandiko WM, Marete I, et al. Evaluating a patient-centred
intervention to increase disclosure and promote resilience for children living
with HIV in Kenya. Aids 2019; 33(Suppl. 1):S93 –s101.
36. Jefferies P, Ungar M, Aubertin P, et al. Physical literacy and resilience in
children and youth. Front Public Health 2019; 7:346.
37. Kirby N, Wright B, Allgar V. Child mental health and resilience in the context
of socioeconomic disadvantage: results from the Born in Bradford cohort
study. Eur Child Adolesc Psychiatry 2020; 29:467–477.
38. Hu YQ. Development and psychometric validity of the resilience scale for
Chinese adolescents development and psychometric validity of the resilience
scale for Chinese adolescents. Acta Psychol Sin 2008; 40:902 –912.
39. Xiao Y, Wang Y, Chang W, et al. Factors associated with psychological
resilience in left-behind children in southwest China. Asian J Psychiatr 2019;
46:1– 5.
40.
&
Tam CC, Li X, Benotsch EG, et al. A resilience-based intervention pro-
gramme to enhance psychological well being and protective factors for rural-
to-urban migrant children in China. Appl Psychol Health Well Being 2020;
12:53– 76.
This was an RCT study where children were randomly assigned to either a
resilience-based intervention group or the wait-list control group. Although it
was predicted that lower depression scores would result postintervention, several
instruments were used to measure resilience-related protective factors. Culturally
specific measures were also used.
41. Morgan T, Yang S, Liu B, et al. A comparison of psychological resilience and
related factors in Chinese firstborn and only children. Asian J Psychiatr 2020;
53:102360.
42. Liu H, Liu L, Jin X. The impact of parental remote migration and parent– child
relation types on the psychological resilience of rural left-behind children in
china. Int J Environ Res Public Health 2020; 17:5388.
43. Achenbach TM, Edelbrock C. Manual for the child behavior checklist and
revised child behavior profile. Burlington, VT: Queen City Printers; 1983.
44. Achenbach TM, Rescorla LA. Manual for the ASEBA school-age forms &
profiles, in Research Center for Children, Youth & Families. Burlington, VT:
University of Vermont; 2001.
45. Malee KM, Kerr S, Paul R, et al. Emotional and behavioral resilience among
children with perinatally acquired HIV in Thailand and Cambodia. Aids 2019;
33(Suppl 1):S17– s27.
46.
&
Conover KM. Tell Me A Story: promoting resiliency in military children with a
bibliotherapy intervention. Nurs Forum 2020; 55:439 –446.
This was an intervention study where both positive and negative outcomes were
examined. A bibliotherapy type of intervention was used where parents were
shown how to use story-telling to address difficult topics. Postintervention, two
instruments were used to assess resilience, whereas one instrument was used to
measure emotional and behavioral problems.
47.
&
Cui Z, Oshri A, Liu S, et al. Child maltreatment and resilience: the promotive
and protective role of future orientation. J Youth Adolesc 2020;
49:2075– 2089.
This longitudinal study had a generous sample size of 1354 children that were
followed since birth. In addition to using several instruments to measure both
positive and negative outcomes from ages 14 to 18, child maltreatment was also
measured every two years from birth onward.
48. Ndetei D, Mutiso V, Maraj A, et al. Towards understanding the relationship
between psychosocial factors and ego resilience among primary school
children in a Kenyan setting: a pilot feasibility study. Comm Ment Health J
2019; 55:1038– 1046.
49. Rosenberg M. Society and the adolescent self-image. Princeton, NJ: Prin-
ceton University Press; 1965.
Mood and anxiety disorders
20 www.co-psychiatry.com Volume 34 Number 1 January 2021
Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved.
50. Liebenberg L, Ungar M, LeBlanc JC. The CYRM-12: a brief measure of
resilience. Can J Public Health 2013; 104:e131 –e135.
51. Ungar M, Liebenberg L. Assessing resilience across cultures using mixed
methods: construction of the child and youth resilience measure. J Mixed
Methods Res 2011; 5:126– 149.
52. Hebbani S, Ruben JP, Selvam S, et al. A study of resilience among young
adult children of alcoholics in Southern India. J Addict Dis 2020;
38:339– 347.
53. Connor KM, Davidson JR. Development of a new resilience scale: the
Connor-Davidson Resilience Scale (CD-RISC). Depress Anxiety 2003;
18:76– 82.
54. Campbell-Sills L, Stein MB. Psychometric analysis and refinement of the
Connor– Davidson Resilience Scale (CD-RISC): validation of a 10-item
measure of resilience. J Trauma Stress 2007; 20:1019– 1028.
55. Ryff CD, Keyes CL. The structure of psychological well bei ng revisited. J Pers
Soc Psychol 1995; 69:719–727.
56. Young JM, Vandewouw MM, Whyte HE, et al. Resilience and vulnerability:
neurodevelopment of very preterm children at four years of age. Front Hum
Neurosci 2020; 14:219.
57.
&&
Gartland D, Riggs E, Muyeen S, et al. What factors are associated with
resilient outcomes in children exposed to social adversity? A systematic
review. BMJ Open 2019; 9:e024870.
This review examined thirty articles published between 2004 and 2018 for which
the focus was individual, family, and social factors associated with resilient out-
comes in children in the context of a broad range of adversities.
58. Althubaiti A. Information bias in health research: definition, pitfalls, and
adjustment methods. J Multidiscip Healthc 2016; 9:211 –217.
59. Korelitz KE, Garber J. Congruence of parents’ and children’s perceptions of
parenting: a meta-analysis. J Youth Adolesc 2016; 45:1973 –1995.
60. De Los Reyes A. Strategic objectives for improving understanding of
informant discrepancies in developmental psychopathology research. Dev
Psychopathol 2013; 25:669–682.
61. Ho SM, Ho JW, Bonanno GA, et al. Hopefulness predicts resilience after
hereditary colorectal cancer genetic testing: a prospective outcome trajec-
tories study. BMC Cancer 2010; 10:279.
62. Gillespie BM, Chaboyer W, Wallis M, et al. Resilience in the operating room:
developing and testing of a resilience model. J Adv Nurs 2007; 59:427 –438.
63. Cicchetti D. Resilience under conditions of extreme stress: a multilevel
perspective. World Psychiatry 2010; 9:145 –154.
64. Smiley PA, Dweck CS. Individual differences in achievement goals among
young children. Child Dev 1994; 65:1723–1743.
65. Ziegert DI, Kistner JA, Castro R, et al. Longitudinal study of young children’s
responses to challenging achievement situations. Child Dev 2001;
72:609– 624.
66. Cole DA, Warren DE, Dallaire DH, et al. Early predictors of helpless thoughts
and behaviors in children: developmental precursors to depressive cogni-
tions. Clin Child Psychol Psychiatry 2007; 12:295 –312.
67. Foster K, Mitchell R, Van C, et al. Resilient, recovering, distressed: a long-
itudinal qualitative study of parent psychosocial trajectories following child
critical injury. Injury 2019; 50:1605–1611.
68. Park CL, Dibble KE, Sinnott S, et al. Chapter 8 - Resilience trajectories of
cancer survivors: a meaning-making perspective. Navigating Life Transitions
for Meaning. 2020; 129– 144.
69. Quale AJ, Schanke AK. Resilience in the face of coping with a severe physical
injury: a study of trajectories of adjustment in a rehabilitation setting. Rehabil
Psychol 2010; 55:12– 22.
70. Wakschlag LS, Briggs-Gowan MJ, Hill C, et al. Observational Assessment of
Preschool Disruptive Behavior, Part II: validity of the Disruptive Behavior
Diagnostic Observation Schedule (DB-DOS). J Am Acad Child Adolesc
Psychiatry 2008; 47:632–641.
71. Wakschlag LS, Hill C, Carter AS, et al. Observational Assessment of Pre-
school Disruptive Behavior, Part I: reliability of the Disruptive Behavior
Diagnostic Observation Schedule (DB-DOS). J Am Acad Child Adolesc
Psychiatry 2008; 47:622–631.
72. Charmandari E, Tsigos C, Chrousos G. Endocrinology of the stress re-
sponse. Annu Rev Physiol 2005; 67:259 –284.
73. Charil A, Laplante DP, Vaillancourt C, et al. Prenatal stress and brain
development. Brain Res Rev 2010; 65:56–79.
74. Sandman CA, Wadhwa PD, Dunkel-Schetter C, et al. Psychobiological
influences of stress and HPA regulation on the human fetus and infant birth
outcomes. Ann NY Acad Sci 1994; 739:198 –210.
75. Weaver IC, Cervoni N, Champagne FA, et al. Epigenetic programming by
maternal behavior. Nat Neurosci 2004; 7:847 –854.
76. Lemaire V, Lamarque S, Le Moal M, et al. Postnatal stimulation of the pups
counteracts prenatal stress-induced deficits in hippocampal neurogenesis.
Biol Psychiatry 2006; 59:786– 792.
77. Buss C, Lord C, Wadiwalla M, et al. Maternal care modulates the relationship
between prenatal risk and hippocampal volume in women but not in men. J
Neurosci 2007; 27:2592– 2595.
78. Dow-Edwards D, MacMaster FP, Peterson BS, et al. Experience during
adolescence shapes brain development: from synapses and networks to
normal and pathological behavior. Neurotoxicol Teratol 2019; 76:106834.
79. Wierenga LM, Bos MG, Schreuders E, et al. Unraveling age, puberty and
testosterone effects on subcortical brain development across adolescence.
Psychoneuroendocrinology 2018; 91:105–114.
80. Holt-Lunstad J. Why social relationships are important for physical health: a
systems approach to understanding and modifying risk and protection. Annu
Rev Psychol 2018; 69:437– 458.
81. Landry SH, Smith KE, Swank PR. Responsive parenting: establishing early
foundations for social, communication, and independent problem-solving
skills. Dev Psychol 2006; 42:627–642.
82. Bowlby J. Attachment and loss: retrospect and prospect. Am J Orthopsy-
chiatry 1982; 52:664– 678.
83. Daskalakis NP, Bagot RC, Parker KJ, et al. The three-hit concept of vulner-
ability and resilience: toward understanding adaptation to early-life adversity
outcome. Psychoneuroendocrinology 2013; 38:1858–1873.
84. Hartman S, Belsky J. Prenatal programming of postnatal plasticity revisited:
and extended. Dev Psychopathol 2018; 30:825 –842.
85. Matthey S, Petrovski P. The Children’s Depression Inventory: error in cutoff
scores for screening purposes. Psychol Assess 2002; 14:146 –149.
86. Manly JT, Cicchetti D, Barnett D. The impact of subtype, frequency, chroni-
city, and severity of child maltreatment on social competence and behavior
problems. Dev Psychopathol 1994; 6:121 –143.
87. Stein MB, Campbell-Sills L, Gelernter J. Genetic variation in 5HTTLPR is
associated with emotional resilience. Am J Med Genet B Neuropsychiatr
Genet 2009; 150B:900–906.
88. Cicchetti D, Rogosch FA. Gene Environment interaction and resilience:
effects of child maltreatment and serotonin, corticotropin releasing hormone,
dopamine, and oxytocin genes. Dev Psychopathol 2012; 24:411 –427.
89. van Winkel M, Peeters F, van Winkel R, et al. Impact of variation in the BDNF
gene on social stress sensitivity and the buffering impact of positive emo-
tions: replication and extension of a gene-environment interaction. Eur
Neuropsychopharmacol 2014; 24:930–938.
90. Nederhof E, Bouma EM, Riese H, et al. Evidence for plasticity genotypes in a
gene-gene-environment interaction: the TRAILS study. Genes Brain Behav
2010; 9:968– 973.
91. Polanczyk G, Caspi A, Williams B, et al. Protective effect of CRHR1 gene
variants on the development of adult depression following childhood maltreat-
ment: replication and extension. Arch Gen Psychiatry 2009; 66:978– 985.
92. Woody ML, Kudinova AY, McGeary JE, et al. Influence of maternal depres-
sion on children’s brooding rumination: moderation by CRHR1 TAT haplo-
type. Cogn Emot 2016; 30:302–314.
93. Das D, Cherbuin N, Tan X, et al. DRD4-exonIII-VNTR moderates the effect of
childhood adversities on emotional resilience in young-adults. PLoS One
2011; 6:e20177.
94.
&&
Niitsu K, Rice MJ, Houfek JF, et al. A systematic review of genetic influenc e on
psychological resilience. Biol Res Nurs 2019; 21:61 –71.
This important review article summarizes 10 studies that examined common
genotypes associated with psychological resilience. Six genetic variants were
identified: 5-HTTLPR, DRD4, BNDF, CRHR1, the oxytocin receptor and regulator
of G-protein signaling 2.
95.
&
Elbau IG, Cruceanu C, Binder EB. Genetics of resilience: gene-by-environ-
ment interaction studies as a tool to dissect mechanisms of resilience. Biol
Psychiatry 2019; 86:433–442.
This review discusses the importance of using gene-by-environment interaction studies
to study resilience. Critiques of the diathesis-stress model and candidate gene
approaches are addressed and other molecular methods are reviewed and s uggested.
96. Belsky J, Jonassaint C, Pluess M, et al. Vulnerability genes or plasticity
genes? Mol Psychiatry 2009; 14:746–754.
97. Assary E, Vincent JP, Keers R, et al. Gene-environment interaction and
psychiatric disorders: review and future directions. Semin Cell Dev Biol
2018; 77:133– 143.
98. Jolicoeur-Martineau A, Wazana A, Szekely E, et al. Alternating optimization for
GE modelling with weighted genetic and environmental scores: examples
from the MAVAN study. Psychol Methods 2019; 2:196 –216.
99. Belsky J, Pluess M. Beyond risk, resilience, and dysregulation: phenotypic
plasticity and human development. Dev Psychopathol 2013; 25:1243–1261.
100. Belsky J, Pluess M. Beyond diathesis stress: differential susceptibility to
environmental influences. Psychol Bull 2009; 135:885 –908.
101. Herbell K, Breitenstein SM, Melnyk BM, et al. Family resilience and flourish-
ment: well being among children with mental, emotional, and behavioral
disorders. Res Nurs Health 2020; 43:465 –477.
Measuring resilience in children King et al.
0951-7367 Copyright ß2020 Wolters Kluwer Health, Inc. All rights reserved. www.co-psychiatry.com 21