Content uploaded by The Late Pieter Rossouw
Author content
All content in this area was uploaded by The Late Pieter Rossouw on May 19, 2016
Content may be subject to copyright.
INTERNATIONAL JOURNAL OF NEUROPSYCHOTHERAPY Volume 4 Issue 1 (2016)
31
research
The Predictive 6-Factor Resilience Scale:
Neurobiological Fundamentals and Organizational Application
Pieter J. Rossouw and Jurie G. Rossouw
Abstract
Psychological resilience is currently viewed as primarily a mental construct, with few measurement scales explic-
itly considering health hygiene factors as an integral component that allows healthy adaptation to adversity. On-
going research, however, has provided greater clarity on the neurobiological nature of psychological resilience and
has also suggested that health hygiene factors aect mental well-being on a neurobiological basis. We describe the
neurobiological fundamentals of a new brief psychological resilience rating scale, the Predictive 6-Factor Resilience
Scale (PR6), consisting of 16 items. Using this scale, we test the hypothesis that health hygiene factors are correlat-
ed with psychological resilience domains. We also measure forward-looking elements to contrast with point-in-
time measurements and to check for consistency with the resilience construct. An existing neurobiological model
is used as the basis for resilience domains and is then compared to other resilience scales for similarity in domain
coverage. e PR6 was developed and subsequently applied using two modes (digital delivery, paper-based) to
groups of working professionals (Healthcare, Finance). Internal consistency of the PR6 was tested and correlations
between health hygiene factors and current resilience domains were carried out. Dierences in resilience between
industry, gender, and age groups were considered. Resilience scores for the PR6 showed good internal consistency
over the 16 items and, alongside the correlation studies, conrmed that health hygiene factors have a statistically
signicant relationship with psychological resilience. Domain variances in groups indicated lower health hygiene
scores in the Finance industry group, as well as with males. Emotion regulation (Composure domain) was found
to be higher in the Healthcare industry group. Forward-looking items were also found to improve consistency
and correlate with higher levels of resilience. Findings suggest that health hygiene factors should be considered
in conjunction with traditional psychological resilience domains, and that the PR6 is a valid psychometric scale
through which measurement can be applied. Forward-looking items (approach/ avoidance motivation schemas)
were found to have a strong positive correlation with overall resilience scores, suggesting approach motivation
schemas favorably impact healthy adaptation to dicult circumstances and stress. e foundations of each re-
silience domain measured by the PR6 provide for targeted treatment to improve holistic resilience capacity, and
industry application in this study shows ecacy for both point-in-time and forward-looking psychological resil-
ience assessment.
32
INTERNATIONAL JOURNAL OF NEUROPSYCHOTHERAPY Volume 4 Issue 1 (2016)
Author information:
Pieter J Rossouw, BA, Hons, MClin Psych, PhD; Professor, Brain Based Education, School of Education, Central
Queensland University, Australia; Director, e Neuropsychotherapy Institute; Director, Mediros; Director, e BrainGro
Institute.
Jurie Rossouw, BCom Risk; Director, RForce.
Correspondence concerning the article should be sent to Pieter Rossouw, School of Education, Central Queensland
University, Rockhampton, QLD, 4072. Email: p.rossouw@cqu.edu.au
Cite as: Rossouw, P. J., & Rossouw, J. G. (2016). e predictive 6-factor resilience scale: Neurobiological
fundamentals and organizational application. International Journal of Neuropsychotherapy, 4(1), 31–45. doi:
10.12744/ijnpt.2016.0031-0045
Mental health disorders are estimated to
cost U.S. $800 billion in lost productivity
annually, and this amount is expected to
double by 2030 (World Bank, 2014). By extension, this
projected escalation is grounds for giving greater atten-
tion to preventative and protective measures as a poten-
tial long-term avenue for improving mental well-being.
Research over the last three decades into psychological
resilience has indicated that this may be a key compo-
nent in the challenge to attenuate the trend of mental
health disorders (Edward, 2005). Briey, resilience is
the ability to positively adapt and thrive in the face of
risk and adversity (Kong, Wang, Hu, & Liu, 2015; Mas-
ten, Cutuli, Herbers, & Reed, 2009). As a construct, it
exists across multiple domains (Olsson, Bond, Burns,
Vella-Brodrick, & Sawyer, 2003; Rutter, 1985) that are
changeable and dynamic at all stages of the lifespan
(Herrman et al., 2011). Rutter (2012) has noted that the
focus is on individual dierences, indicating the impor-
tance of accurately measuring variances within groups
for ecacious intervention.
While a host of resilience measurement scales have
been developed in the last two decades (Windle, Ben-
nett, & Noyes, 2011), any adaptation of scales based on
ndings from neurobiology research or related ndings
in research on physiological well-being has not been
readily apparent. Deeper integration of these elds with
resilience measurement could assist in moving the re-
search beyond primarily phenomenological observa-
tions toward a mechanistic understanding of resilience
capacity (Russo, Murrough, Han, Charney, & Nestler,
2012). is approach may reveal methods of interven-
tion that are not currently in the arsenal for combat-
ing the rise of mental health disorders as projected by
the World Bank (2014), for example. Recognizing this
need, the World Health Organization has set a target
of a 20% increase in service coverage for mental disor-
ders by 2020 (World Health Organization, 2015). e
broad applicability of resilience as a protective measure
against depression across the lifespan (Elisei, Sciarma,
Verdolini, & Anastasi, 2013) makes it a valuable inter-
vention avenue, not only in clinical applications but also
in workplaces, schools, and other organizations where
the wider population can be reached.
In this paper we investigate theoretical connections
between domains of resilience and a neurobiological
model to establish a new resilience measurement scale
(Rossouw, 2015). We examine the implications of this
scale: For example, given the importance of adaptation
to resilience, together with the role of neuroplasticity
to facilitate this adaptation, we hypothesize there exists
a correlation between health factors that promote both
neuroplasticity and psychological resilience.
As noted by Fredrickson and Branigan (2012), “e
broadening and undoing eects of positive emotion
might together account for the salutary eects of pos-
itive emotions on health, physical functioning and lon-
gevity” (para. 31). With regard to resilience, there may
be a bidirectional relationship where positive health
promotes feelings of condence and ability to deal with
adverse situations (Tugade, Fredrickson, & Barrett,
2004). An analysis of the major resilience scales indi-
cates that, to date, the potential relationship between
resilience and health factors has not been incorporat-
ed into their designs. Consequently, we further explore
the potential for psychological approach and avoidance
patterns to be predictive in determining the future di-
rection of psychological development, particularly in
INTERNATIONAL JOURNAL OF NEUROPSYCHOTHERAPY Volume 4 Issue 1 (2016)
33
relation to resilience and well-being (Elliot & Coving-
ton, 2001). e culmination of these factors is the Pre-
dictive 6-Factor Resilience Scale (PR6) described below.
Method
Development of the Scale
e wealth of research conducted in the development
of existing resilience scales, particularly the higher scor-
ing scales described in a recent review by Windle et al.
(2011)—and in light of their assertion that, as yet, there
exists no gold standard for resilience—allows the PR6
to be developed in a harmonious manner. e domains
established in the PR6 may thus be in alignment with
those described in the literature and in existing scales.
is alignment provides a foundation that we can use to
connect to a neurobiological model to establish a resil-
ience scale that is more holistic and inclusive in scope.
Measurement is at an individual level and aims to ex-
amine protective factors to mitigate risk and adversity,
leading to thriving and resilient outcomes beyond what
would normally be expected.
As a mental construct, resilience is underpinned
by neural networks and neurobiological functioning
(Russo et al., 2012) and is known to change dynamical-
ly through various stages of life (Herrman et al., 2011).
erefore, while resilience is a function that helps indi-
viduals adapt, psychological resilience itself adapts over
time (Donnon & Hammond, 2007; Friborg, Hjemdal,
Rosenvinge, & Martinussen, 2003; Oshio, Kaneko, Nag-
amine, & Nakaya, 2003; Windle, Markland, & Woods,
2008). is adaptive capacity is enabled through well-es-
tablished concepts of neuroplasticity as inuenced by
environmental factors (Kandel, 1998; Kandel, Schwartz,
Jessell, Siegelbaum, & Hudspeth, 2013). Plasticity func-
tions mechanistically via brain-derived neurotroph-
ic factor (BDNF), which elevates neural production
and, in turn, neural proliferation, to strengthen either
healthy approach patterns or maladaptive avoidance
patterns depending on the current neural activation
(Castrén & Rantamäki, 2010; Lu, Nagappan, Guan, Na-
than, & Wren, 2013). Given the crucial role of BDNF in
neural development on a temporal scale, it follows that
factors that positively aect the production of BDNF—
such as physiological health hygiene—would positively
correlate with the construct of resilience and, accord-
ingly, introduce a new domain. is domain may indi-
cate a virtuous interplay between traditional markers of
psychological resilience and physiological health fac-
tors that positively inuence BDNF and neural prolifer-
ation. We investigate this domain alongside traditional
domains of resilience as described in the existing scales
and the literature.
Domains of the PR6
Domains were formed based on the expansive na-
ture of traits within the construct of resilience, allowing
for more insightful thematic trait groupings that share
neurological underpinnings. A neurobiological model
that has previously been explored in the context of re-
silience is Davidson’s six dimensions of emotional styles
(Davidson & Begley, 2012; Rossouw, 2013). A theoret-
Table 1
Domain Alignment Between the PR6 and Existing Resilience Scales
PR6 domains Davidson Styles RSA CDRISC READ RS ARS RASP DRS YRADS CYRM CHKS
Vision Outlook style
Composure Self-awareness style
Tenacity Resilience style
Reasoning Attention style
Collaboration Social Intuition style
Sensitivity to context style *
Health -
Windle et al. Score 7 7 6 6 4 4 4 3 3 2
Note. RSA = Resilience Scale for Adults; CDRISC = Connor Davidson Resilience Scale; READ = Resilience Scale for Adolescents; ARS = Adolescent
Resilience Scale; RASP = Resilience Attitudes and Skills Prole; DRS = Dispositional Resilience Scale; YRADS = Youth Resiliency: Assessing Devel-
opmental Strengths; CYRM = Child and Youth Resilience Measure; CHKS = California Healthy Kids Survey.
*Existential aloneness.
34
INTERNATIONAL JOURNAL OF NEUROPSYCHOTHERAPY Volume 4 Issue 1 (2016)
ical analysis and comparison of this model with exist-
ing scales, illustrated in Table 1, indicates a synthesis of
interpersonal and intrapersonal protective factors that
can be adapted into ve domains of psychological resil-
ience. ese ve domains are complemented by a sixth
domain relating to physiological health. Interpretive
and grouping dierences between approaches result in
subjective domain sorting; however, we hold that su-
cient thematic alignment exists to analyze and catego-
rize. As indicated in Table 1, some resilience scales do
not clearly represent every domain described.
e rst domain (Vision) includes concepts of
self-ecacy and goal setting. Both the Resilience Scale
for Adults (RSA) and the Resilience Scale for Adoles-
cents (READ) indicate Personal Competence as a fac-
tor that aligns to this trait group (Friborg et al., 2003;
Hjemdal, Friborg, Stiles, Martinussen, & Rosenvinge,
2006). Likewise, a review of the Connor–Davidson Re-
silience Scale (CD–RISC) found Personal Competence,
Sense of Control, and High Standards to be related
characteristics (Connor & Davidson, 2003). e Dis-
positional Resilience Scale (DRS) also includes Control
alongside Commitment (Hystad, Eid, Johnsen, Laberg,
& Bartone, 2010). e Resilience Attitudes and Skills
Prole (RASP) describes Creativity in relation to goals
alongside Initiative and Values Orientation (Hurtes &
Allen, 2001). e Youth Resiliency: Assessing Develop-
mental Strengths (YRADS) scale aligns with Self-Con-
cept and Empowerment (Donnon & Hammond, 2007).
Similarly, the California Health Kids Survey (CHKS)
includes Goals and Aspirations alongside Self-Esteem
(Stewart, Sun, Patterson, Lemerle, & Hardie, 2004). e
Resilience Scale (RS) includes Meaningfulness (Wag-
nild & Young, 1993), reecting a sense of purpose and
long-term goals, which aligns well with Positive Future
Orientation in the ARS (Oshio et al., 2003). Conceptu-
ally, these factors align to the Outlook emotional style
identied by Davidson (Davidson & Begley, 2012), re-
ferring to the ability to maintain a positive outlook and
allowing positive emotions to persist—which involves a
positive self-concept, a proclivity to set goals as a path-
way to meaning, and belief in self-worth. It is this sense
of hopefulness, planning, and positive outlook that we
incorporate in the Vision domain. Neurological struc-
tures involved in this domain include the ventral stri-
atum through its role in higher order decision making
and risk/reward cognition (Davidson & Begley, 2012).
e interplay of memory storage and retrieval by the
hippocampus and meaning assignment by the prefron-
tal cortex (PFC) plays a part in maintaining a hopeful
sense of the future, and this is reinforced by goal direct-
edness (Preston & Eichenbaum, 2013).
e second domain (Composure) is primarily about
emotional regulation and the ability to recognize, un-
derstand, and act on internal prompts and physical
signals. e RS reects this as a sense of Equanimity
(Wagnild & Young, 1993) alongside Emotional Regula-
tion in the ARS (Oshio et al., 2003). e RSA and READ
include concepts of Personal Structure (Friborg et al.,
2003; Hjemdal et al., 2006), while the Control aspect
of CD–RISC may also serve in the sense of self-control
(Connor & Davidson, 2003). On the youth resilience
side, RASP describes Humor and Creativity in the con-
text of feelings (Hurtes & Allen, 2001); YRADS speaks of
Self-Control (Donnon & Hammond, 2007); and CHKS
includes Empathy (Stewart et al., 2004). ese align well
to the Self-Awareness emotional style, described by Da-
vidson, which relates neurologically to the ability of the
insula to eectively interpret signals and enable regu-
lation of the hypothalamic–pituitary–adrenal (HPA)
axis (Davidson & Begley, 2012). Self-awareness mani-
fests through increased emotional granularity, where
an accurate and positive disposition has been shown to
improve physiological health through the broaden-and-
build eect and the undoing eect (Tugade et al., 2004).
We group these as the Composure domain.
e third domain (Tenacity) centers on the concept
of perseverance and hardiness, which to many is the
primary characteristic of resilience, and is the main as-
pect measured by the Brief Resilience Scale (Smith et
al., 2008). e CD–RISC describes Tolerance to Neg-
ative Eect and Tenacity (Connor & Davidson, 2003),
while the RS includes Perseverance (Wagnild & Young,
1993). Representation of this aspect is less clear on the
youth measurement scales, but the RASP is supportive
through its concept of Independence (Hurtes & Allen,
2001). e Resilience emotional style from Davidson’s
model presents clear alignment and points to the abil-
ity of the PFC to eectively regulate limbic and HPA
activation (Davidson & Begley, 2012). Here, linkage to
self-awareness can be observed through its role in in-
forming the PFC of the need for HPA regulation. More
broadly, while hardiness may be a key component to
aid in bouncing back from adversity, the other domains
have crucial protective roles to play. Of particular inter-
est in this domain is that perseverance has been shown
to be more important than IQ as a predictor of long-
INTERNATIONAL JOURNAL OF NEUROPSYCHOTHERAPY Volume 4 Issue 1 (2016)
35
term goal outcomes (Duckworth, Peterson, Matthews,
& Kelly, 2007). Considering that broader psychologi-
cal resilience is inclusive of this ability to persevere, we
termed this the Tenacity domain.
e fourth domain (Reasoning) involves a wider
range of higher cognitive traits such as problem-solv-
ing, resourcefulness, and growing through adversity,
or thriving (Carver, 1998). e ARS includes Novel-
ty-Seeking (Oshio et al., 2003) in this light, alongside
an aligning concept of Self-Reliance in the RS (Wagnild
& Young, 1993). CD–RISC refers to the ability to posi-
tively accept change and the strengthening function of
stress (Connor & Davidson, 2003), while the DRS has a
concept titled Challenge (Hystad et al., 2010), and RASP
includes Insight and Creativity in relation to resource-
fulness (Hurtes & Allen, 2001). Other youth scales such
as YRADS include Commitment to Learning (Donnon
& Hammond, 2007), while the Child and Youth Resil-
ience Measure (CYRM) summarizes these as Personal
Skills (Ungar & Liebenberg, 2011). e Attention style
from Davidson’s model is of interest here in its role to
screen out distractions and stay focused when facing
risk or adversity (Davidson & Begley, 2012). Le and
right PFC activation functions in conjunction with the
anterior cingulate cortex (ACC) to rapidly screen for
errors and optimize subsequent responses (Peterson
et al., 2014). Executive functioning here is enabled fol-
lowing the downregulation of the HPA axis through the
Composure and Tenacity domains and functions in the
broader context set by the Vision domain. e ability
to eectively regulate limbic functions is supported by
strategies such as interpretation bias, which has been
shown to have a protective eect in the resilience con-
struct, though it must be grounded in a realistic sense of
optimism (Clarke, 2014; Kleim, örn, & Ehlert, 2014;
Oettingen & Wadden, 1991). We group these traits as
the Reasoning domain, reecting its executive func-
tioning and cognitive nature.
e h domain (Collaboration) relates directly to
psychosocial interaction, including secure attachment,
support networks, context, and humor. is domain
is common among resilience scales, with some scales
focusing more heavily on this aspect. For example, the
RSA and READ include Social Competence, Family Co-
herence, and Social Resources, making up the bulk of
these surveys (Friborg et al., 2003; Hjemdal et al., 2006).
CD–RISC contains Secure Relationships (Connor &
Davidson, 2003), while the RS contrasts with Existential
Aloneness (Wagnild & Young, 1993). Youth scales are
also heavy on this aspect, with YRADS listing Parental
Support/Expectations, Peer Relationships, Community
Cohesiveness, School Culture, Cultural Sensitivity, and
Social Sensitivity (Donnon & Hammond, 2007). RASP
describes Relationships and Humor in this context
(Hurtes & Allen, 2001), while CYRM includes Social
Skills and Peer Support (Ungar & Liebenberg, 2011).
Finally, CHKS aligns with Help-Seeking and Com-
munication and Cooperation in this group (Stewart et
al., 2004). ese align with two of the Davidson styles,
namely Social Intuition, which refers to the ability to ac-
curately read people through body language, emotional
tone, and needs, and Sensitivity to Context, which in-
volves being able to accurately discriminate between so-
cial contexts and adapt approach accordingly (Davidson
& Begley, 2012). Schore (2000) noted that the right pre-
frontal cortex (RPFC), which receives cues interpreted
by other regions, plays a key role in secure attachment.
It has been suggested that the fusiform gyrus plays this
interpretive role through facial expression recognition
and has been shown to be able to aect the amygdala in
response to emotional faces (Pujol et al., 2009). Healthy
RPFC interpretation and accurate facial recognition
are thus crucial to appropriately regulating amygdala
activation for constructive reaction when faced with
risk and adversity. On a broader level, secure attach-
ment is well documented as a key component of resil-
ience (Blaustein & Kinniburgh, 2010; Svanberg, 1998).
is positive impact of the social framework continues
through adolescence and into adult life, where research
has shown social inuences aect BMI and weight loss
outcomes (Leahey, Kumar, Weinberg, & Wing, 2012;
Leahey, LaRose, Fava, & Wing, 2011). Of particular
interest is that it is not received support but rather the
perception of support that is the key enabler of resilient
outcomes (Wethington & Kessler, 1986). is reinforces
the importance of healthy neural activation in the PFC
to regulate triggers that may otherwise cause distress—
and thereby maintain wellness through positive inter-
pretation and perception management. Multifaceted
and complex, we title this the Collaboration domain.
Proposed Domain: Health Hygiene Factors
e sixth domain (Health) concerns physiological
health and is the proposed addition. While the other
ve domains are heavily informed by current resilience
scales, this sixth domain has received little attention,
36
INTERNATIONAL JOURNAL OF NEUROPSYCHOTHERAPY Volume 4 Issue 1 (2016)
likely due to a focus on the psychological aspects of re-
silience. Work by Tugade et al. (2004) clearly indicated
a link between emotional experience and health—for
example, calling on the eect of higher resilience to
quell autonomic arousal in the HPA. is type of arous-
al increases cortisol levels, which in turn reduces BDNF
and thereby the potential for positive neural adaptation
(Issa, Wilson, Terry, & Pillai, 2010). Evidence of chronic
health issues aecting mood, and the relationship be-
tween posttraumatic stress disorder, anxiety, and neg-
ative health outcomes, strengthen the hypothesis of a
link between positive health and resilience (Eckenrode,
1984; McWilliams, Cox, & Enns, 2003). is is especial-
ly relevant since resilient individuals have been shown
to be better at coping with serious health issues such
as cancer (Min et al., 2013). We turn now to the posi-
tive eect of BDNF on resilience and nd three physio-
logical factors that aect production. We also consider
another factor beyond BDNF that also has a potential
interconnection with resilience.
e rst factor is regular exercise, which has been
shown to increase BDNF and hippocampal function
(Cassilhas et al., 2012; Cotman & Berchtold, 2002). In
the short term, exercise improves cognitive and memo-
ry functions (Chapman et al., 2013), as well as ACC ac-
tivation, which is key for the Reasoning domain. Bene-
ts also extend into the long term to maintain cognitive
capacities and serve to protect against future adversity
in the form of mental decline (Colcombe et al., 2006).
e second factor is nutrition, as a diet high in sugar,
dietary fats, and alcohol has been show to downregu-
late BDNF (Heernan, 2008; Molteni, Barnard, Ying,
Roberts, & Gomez-Pinilla, 2002). More generally, the
psychological link between the broader inuence of
nutrition and well-being is well established, such as the
strong relationship between obesity and depression (Si-
mon et al., 2008).
e third factor is sleep hygiene, where recent evi-
dence points to a crucial interplay between stress, sleep,
and BDNF levels (Giese, Unternaehrer, Brand, Cal-
abrese, Holsboer–Trachsler, & Eckert, 2013). Lack of
sleep has further been shown to degrade higher cogni-
tive functioning along with increasing impulsiveness,
which may lead to negative outcomes when faced with
adversity requiring reasoned responses (Greer, Gold-
stein, & Walker, 2013; Killgore, 2010). e recommended
quantity of sleep is inversely related to age—currently
it is eight to ten hours for teenagers and seven to nine
hours for adults (Hirshkowitz et al., 2015).
In combination, these three factors designate ade-
quate health hygiene factors to be included as items in
the PR6. We include an item per factor, as well as an
item for overall health, as even the best hygiene may not
protect against all physiological problems—for exam-
ple, a general health self-report survey has shown high
correlation with chronic pain (Mäntyselkä, Turunen,
Ahonen, & Kumpusalo, 2003).
Approach/Avoidance Motivation
Motivation in terms of approach and avoidance sug-
gest a distinction between behaviors of approach, where
reward is expected, and avoidance, where there is a fear
of loss (Elliot & Covington, 2001). In the context of high
resilience, one would expect the approach–avoidance
conict to result in constructive outcomes. Some ap-
proach and avoidance models have been found useful
predictors of work and educational outcomes as well as
dysfunctional outcomes (Jackson, Hobman, Jimmieson,
& Martin, 2009). Continued goal striving during adver-
sity is a constructive product of resilience. As Elliot and
rash (2002) summarize, a goal is “a concrete cogni-
tive representation of a desired or undesired end state
use to guide behaviour” (p. 806), and they go on to con-
nect an approach temperament to positive prediction of
goal outcomes. Two items are included in the scale to
measure approach and avoidance schemas in terms of a
sense of direction and openness to new challenges. is
is measured in conjunction with the other six domains
as Momentum.
Survey Design
e survey was envisioned as a shorter form self-re-
port questionnaire to increase its applicability to broad-
er contexts and allow for re-testing over time. is
follows precedent and preempts the path followed by
previous scales (Burns & Anstey, 2010; Carver, 1997;
Smith et al., 2008). Items were rated on a 5-point Likert
scale ranging from 1 = not at all like me (most nega-
tive), 2 = a bit like me, 3 = somewhat like me, 4 = of-
ten like me, and 5 = very much like me (most positive).
Two of the Health domain questions had more specic
answers, again ranging across 5 points. Two items were
selected per domain which were informed by a review
of existing scales as well as additional literature on the
INTERNATIONAL JOURNAL OF NEUROPSYCHOTHERAPY Volume 4 Issue 1 (2016)
37
subject of resilience. Item revision was also conducted
via feedback from the rst group of study participants,
resulting in minor revisions of wording for items relat-
ing to Composure. Each domain (except for the Health
domain) and the Momentum items contained one re-
verse-scored question; the Health domain comprised
four positively scored items. Table 2 expands on de-
scriptions of each item within the PR6.
Study Sample
e overall sample (N = 204) consisted of two groups
of professionals recruited to complete the survey. e
rst group (n = 128) consist-
ed primarily of Healthcare
and Education professionals
contacted during workshops
in the following cities: in Aus-
tralia: Melbourne (59), Syd-
ney (29), and Brisbane (26);
in New Zealand: Dunedin
(14). Surveys were completed
on paper sheets handed out
and then handed back to the
facilitator once completed.
Of this group, 80% were psy-
chology clinicians or coun-
sellors. Males accounted for
13% of the sample, females
78%, while the remaining
9% marked “other” or le a
blank. Age representation
was broad: 9% were between
21 and 30 years of age, 18%
between 31 and 40, 27% be-
tween 41 and 50, and 44% were 50 and over.
e second group (FIN) consisted of nancial ser-
vices professionals recruited from a major bank (n =
76). e survey was oered to the organization in the
form of an online device completed condentially by
each sta member. Individual results were not made
available to management. e respondents all resided
in Sydney; females accounted for 41% and males 59%
of the total group. Age representation was again broad,
with 5% aged between 21 and 30, 43% between 31 and
40, 34% between 41 and 50, and 5% were 50 years and
over.
Table 2
The Predictive 6-Factor Resilience Scale
Item Description Scoring
1, 7* Tenacity domain 1 2 3 4 5
2*, 8 Vision domain 1 2 3 4 5
3, 9* Collaboration domain 1 2 3 4 5
4, 10* Composure domain 1 2 3 4 5
5, 11* Reasoning domain 1 2 3 4 5
6*, 12 Momentum 1 2 3 4 5
13, 14, 15, 16 Health domain 1 2 3 4 5
*Reverse scored.
Figure 1. Histogram of overall resilience scores across all groups.
38
INTERNATIONAL JOURNAL OF NEUROPSYCHOTHERAPY Volume 4 Issue 1 (2016)
Results
Scoring was completed by rst reversing the neg-
atively phrased questions, then summing each item
pair per the rst ve domains and for the Momentum
score. Health had four positively scored items, which
were subsequently summed to complete the scores for
the six domains. Each domain was averaged to produce
a comparable score per domain. An overall resilience
score (PR6 score) was calculated as an average of each
of the six domains, ranging from 0 (lowest resilience) to
1 (highest resilience).
e distribution of PR6 scores for N = 204 (Figure 1)
resulted in M = 0.6879, SD = 0.117, and 95% CI [0.67178,
0.70409]. e results mostly followed the SD, with addi-
tional clustering around the 75th and 85th percentiles.
Normality was conrmed with an Anderson–Darling
test of 0.440 and a p-value of 0.289 for the full popula-
tion. Floor and ceiling eects were not encountered as
no responses reached the lowest level, while only one
response reached near the upper bound with a score of
0.9911.
Group Analysis
Table 3 summarises scores for the dierent popula-
tions across Industry, Age, and Gender.
Industry-grouped PR6 scores for Healthcare at M =
0.697 were slightly higher than Finance at M = 0.6842,
though both fell within 95% CI, indicating no statisti-
cally signicant dierence, while Education and Not
Specied scores at the time of measurement did not
have sucient data to draw meaningful conclusions.
Similar results were observed within Age, Gender, and
Location whereas once a sucient number of responses
had been received, no statistically signicant dierenc-
es were noted within groups for overall scores. Domain
analysis indicated one statistically signicant dierence
between Finance and Healthcare. Composure scores,
95% CI [0.6262, 0.6863], for Healthcare were signi-
cantly higher (M = 0.6971, p = 0.027). Health scores,
95% CI [0.6047, 0.6613], for Finance were lower, but the
dierence was not statistically signicant (M = 0.5921,
p > 0.05).
Overall, mean PR6 scores for females were 0.6823,
with males scoring slightly higher at 0.6983. Males had
higher variability, ranging from a minimum of 0.2857
to a maximum of 0.9911, compared to females with a
minimum of 0.3393 to a maximum of 0.9464. Figure 2
shows PR6 scores by gender and age group. Initial re-
sults indicated stability among female age groups, while
males appeared to have an upward trajectory over time.
However, the low number of results for males ages 21-
30 (n = 2) and 50+ (n = 12) suggest additional data is
required before signicance can be validated.
Figure 3 shows gender dierences by domain of resil-
ience. is analysis indicated an area of statistically sig-
nicant dierence between genders. Within the Health
domain, 95% CI [0.6047, 0.6613], compared to females,
Table 3
Statistics Summary of Resilience Scores Within Groups
Industry N MM SEM SD Minimum Q1 Median Q3 Maximum
Healthcare 111 0.697 0.011 0.116 0.3929 0.6161 0.7054 0.7857 0.9464
Finance 76 0.6842 0.0133 0.1157 0.2857 0.625 0.6786 0.7679 0.9911
Education 8 0.6908 0.0295 0.0833 0.5804 0.6094 0.692 0.7366 0.8393
Not specied 9 0.6052 0.0493 0.1478 0.3393 0.4955 0.6339 0.7143 0.8214
Age N M SEM SD Minimum Q1 Median Q3 Maximum
21-30 15 0.656 0.0179 0.0691 0.5357 0.5804 0.6696 0.6875 0.8036
31-40 56 0.688 0.0161 0.1203 0.2857 0.6183 0.7054 0.7589 0.9911
41-50 61 0.6852 0.0155 0.1212 0.3929 0.6027 0.6786 0.7857 0.9107
50+ 60 0.7027 0.0161 0.1244 0.3393 0.6339 0.7054 0.7835 0.9464
Not specied 12 0.6682 0.0263 0.091 0.5179 0.6049 0.6518 0.7612 0.8036
Gender N M SEM SD Minimum Q1 Median Q3 Maximum
Female 131 0.6823 0.0101 0.1151 0.3393 0.5982 0.6786 0.7679 0.9464
Male 62 0.6983 0.0161 0.1267 0.2857 0.6339 0.7054 0.7857 0.9911
Not specied 10 0.7 0.0274 0.0866 0.5 0.6674 0.6964 0.7723 0.8036
Other 1 0.6696 N/A N/A 0.6696 N/A 0.6696 N/A 0.6696
INTERNATIONAL JOURNAL OF NEUROPSYCHOTHERAPY Volume 4 Issue 1 (2016)
39
males scored much lower (M = 0.5696, p = 0.012). Con-
versely, within the Tenacity domain, 95% CI [0.7407,
0.7875], males scored higher (M = 0.7944, p > 0.05),
and in the Reasoning domain, 95% CI [0.6694, 0.7203],
males also scored higher (M = 0.7440, p > 0.05). How-
ever, the high p-values for these dierences noted in the
Tenacity and Reasoning domains indicate statistical sig-
nicance was not reached.
Domain Correlation and Consistency
Domain correlation (Figure 4) shows relationships
between the ve Davidson styles (Vision,
Composure, Reasoning, Tenacity, and
Collaboration) and the proposed Health
domain. e Composure and Reasoning
domains displayed the strongest relation-
ship, while relationships were also evident
between other Davidson styles, as is to be
expected as part of traditional resilience
factors. Of interest is the hypothesized
correlation between the ve Davidson
styles and the proposed Health domain.
Pearson correlation between the Health
domain and ve Davidson styles was
found to be positive at 0.169 with a p-val-
ue of 0.016. While the Pearson value is in
the lower range, the < 0.05 p-value indi-
cates the relation is of statistical signi-
cance. Additional analysis was conduct-
ed to conrm the relationship through
Cronbach’s alpha.
Item analysis yielded a Cronbach’s al-
pha of 0.7364, indicating good internal
consistency and validity as a psychometric
tool. Table 4 details the item analysis and
a if removed from the survey. Of note are
items 3 (openness to working with others)
and 14 (sleep hygiene), which had a slight
negative eect on alpha. e rst 12 ques-
tions (excluding the four Health domain
questions) yielded an alpha of 0.7491.
Additional analysis of the Health do-
main retains alpha above 0.70, indicating
high internal consistency and a mean-
ingful relationship between traditional
resilience domain measurements and the
Health domain. In particular, three of the
questions improve a signicantly: Exer-
cise frequency (Item 15) had the strongest eect (a =
0.719 if omitted); adherence to healthy nutrition (Item
16) had the second strongest eect (a = 0.7295 if omit-
ted); and general perceptions about health (Item 13) had
the third strongest eect (a = 0.723 if omitted).
Forward-looking Momentum items (6, 12) were
found to have a strong positive correlation (Figure 5)
with resilience (Pearson = 0.642, p-value < 0.001). ese
items also had a positive eect on alpha, with Item 6
(reverse scored) and Item 12 reducing alpha to 0.7251
and 0.7173 if omitted. No signicant dierences were
Figure 2. Overall resilience scores per gender and age group.
Note. 1n = 13, 2n = 2, 3n = 12.
Figure 3. Domain scores per gender.
40
INTERNATIONAL JOURNAL OF NEUROPSYCHOTHERAPY Volume 4 Issue 1 (2016)
found in Momentum scores between Industry, Gender,
or Age groupings.
Discussion
We have developed a new holistic resilience scale
(PR6) incorporating health factors through which we
tested the hypothesis that these health factors are an in-
tegral component of psychological resilience. e PR6
was primarily tested on participants in the Healthcare
Table 4
Item Analysis
PR6 Cronbach’s a = 0.7364
Item M*SD
Cronbach’s a if
omitted
1 4.064 0.871 0.7185
2 3.539 1.142 0.7241
3 4.206 0.852 0.7411
4 3.603 0.928 0.7131
5 4.064 0.837 0.7212
6 4.333 0.76 0.7251
7 4.049 0.858 0.7159
8 3.794 0.956 0.7239
9 3.118 1.226 0.7221
10 3.647 1.176 0.7209
11 3.495 1.048 0.7137
12 3.549 0.943 0.7173
13 3.784 0.844 0.723
14 3.598 1.334 0.7478
15 3.245 1.251 0.719
16 3.5 1.201 0.7295
Note. *Likert scale (5-point).
Figure 4. Domain correlation matrix.
Figure 5. Momentum/resilience correlation matrix.
INTERNATIONAL JOURNAL OF NEUROPSYCHOTHERAPY Volume 4 Issue 1 (2016)
41
and Finance industries, rst, to validate the hypothesis
and, second, to investigate its potential for application
among individuals and in the workplace.
Statistically signicant positive correlations between
Health and the ve Davidson styles support the hypoth-
esis that health hygiene factors function together with
traditional resilience constructs. e good internal con-
sistency measurements in this study also support this
hypothesis and conrm that the PR6 represents a val-
id psychological resilience measurement tool. e PR6
unies domains measured by other resilience scales
across ve distinct neurobiological schemas and suc-
cessfully incorporates Health as a new, sixth, domain of
psychological resilience. e positive relationship be-
tween Health and the other ve domains of resilience
is of particular interest because Health is not currently
measured as a standard in any of the scales considered.
As the current view is that resilience is mainly a psycho-
logical construct, the ndings from this study support
the hypothesis that resilience is a wider phenomenon
that also relies on (or manifests as) a predisposition to
maintain healthy habits in terms of exercise frequency,
adherence to health nutrition, and sleeping patterns.
We note that this research does not make a determina-
tion if there is a causative relationship between Health
and the other ve resilience domain, or if one precedes
the other. Interpretation of previous research for the
neurobiological foundations of the PR6 indicate mech-
anistic factors that may explain these relationships in a
causative fashion.
Testing of the scale on a population of professional
workers proved to be a useful application in the mea-
surement and treatment of specic resilience factors.
e diverse industries of Healthcare and Finance dis-
played no statistically signicant dierences in overall
PR6 scores although some dierences were noted on a
domain level—signicantly in the Composure domain,
and to a lower extent in the Health domain. Composure
was noted to be higher in the Healthcare industry, while
Health was noted to be lower in the Finance industry.
Momentum items are noted to be highly consistent
with the resilience construct, suggesting that psycho-
logical approach and avoidance schemas may play a
functional role in the ability to manage adversity. is
suggestion ts with current models, as approach moti-
vation toward changing or adverse circumstances sug-
gests healthy adaptation. Non-Momentum items are
designed to quantify resilience primarily as a point-in-
time measurement, while the Momentum items through
approach and avoidance schemas contrasts with a for-
ward-looking element. is allows particular usefulness
in workplace applications where the Momentum scores
may serve as a leading indicator of future directions of
resilience and well-being.
Furthermore, mapping the PR6 resilience domains to
neurobiological structures indicates more direct poten-
tial brain-based treatment. e addition of health fac-
tors as an integral component of maintaining a healthy
brain and its subsequent eect on the overall resilience
construct further bolsters a holistic resilience treatment
methodology.
Conclusion
e PR6 is a holistic resilience measurement scale
that reaches further than traditional scales by incorpo-
rating health hygiene factors as a fundamental compo-
nent of psychological resilience. Reecting the even-
tual use of existing scales, the scale itself is short and
simple to administer. Application of the scale through
paper-based and electronic administration was found
to have no signicant deviation, allowing for multiple
modes of delivery.
In consideration of dierences in the observed
scores, we note the following speculations. Higher
Composure scores in the Healthcare population are
likely due to 80% of the group being psychology clini-
cians or counsellors who have received specic training
through their professional education. Dierences found
in the Health domain, particularly the lower scores in
Finance, are suspected to be largely related to gender
dierences given that a high percentage of the Health-
care group was female, and female participants overall
had higher Health scores than males.
e signicantly lower Health scores for males, ac-
companied by slightly higher (though not signicant)
scores in Tenacity and Reasoning, suggest that males
may sacrice Health in favor of domains that are more
directly perceived as pursuant to current goals. ese
ndings suggest an area for further research to deter-
mine validity and motivation. e upward trending re-
silience scores as age increases in males, noted in Figure
2, are expected to stabilize to the mean once larger sam-
ple sizes are obtained.
Particular items noted to be less strongly consis-
42
INTERNATIONAL JOURNAL OF NEUROPSYCHOTHERAPY Volume 4 Issue 1 (2016)
tent with resilience were sleep hygiene and openness to
working with others. It may be the case that more re-
silient people are better able to stay focused during pe-
riods of varying sleeping patterns; however, the eects
of chronic sleep disturbance are well documented and
are expected to have an eect on long-term well-being.
Regarding the second item, resilience oen relies on the
assistance of others, but it may not necessarily require
one to actually prefer the company of others. Neverthe-
less, there may be a longer term relationship between
the desire to be around others and protective resilience
factors over time. e authors plan to monitor dierent
versions of these items in order to further investigate
and rene their relationship with resilience.
Ongoing application of the PR6 is planned for young-
er age groups as well as in clinical settings, and this will
be contrasted with treatment to determine eective
methods of resilience modication, focusing especial-
ly on digital delivery methods. e current test across
wide-ranging age groups allows for its application in the
broader population as both an individual and a work-
place resilience and well-being measurement scale, indi-
cating specic strengths and weaknesses across the ho-
listic six domains of resilience. We propose that the six
domains of resilience present discrete neurobiological
components that allow for eective treatment to im-
prove overall resilience and well-being by focusing on
individual areas as highlighted through the PR6.
References
Blaustein, M. E., & Kinniburgh, K. M. (2010). Treating
traumatic stress in children and adolescents: How to
foster resilience through attachment, self-regulation,
and competency. New York, NY: Guilford.
Burns, R. A., & Anstey, K. J. (2010). e Connor–Da-
vidson Resilience Scale (CD–RISC): Testing the in-
variance of a uni-dimensional resilience measure
that is independent of positive and negative aect.
Personality and Individual Dierences, 48, 527–531.
doi:10.1016/j.paid.2009.11.026
Carver, C. S. (1997). You want to measure coping but
your protocol’s too long: Consider the brief COPE.
International Journal of Behavioral Medicine, 4, 92–
10
Carver, C. S. (1998). Resilience and thriving: Issues,
models, and linkages. Journal of Social Issues, 54,
245–266.
Cassilhas, R. C., Lee, K. S., Fernandes, J., Oliveira, M.
G., Tuk, S., Meeusen, R., & de Mello, M. T. (2012).
Spatial memory is improved by aerobic and resis-
tance exercise through divergent molecular mech-
anisms. Neuroscience, 202, 309–317. doi:10.1016/j.
neuroscience
Castrén, E., & Rantamäki, T. (2010). e role of BDNF
and its receptors in depression and antidepressant
drug action: Reactivation of developmental plas-
ticity. Developmental neurobiology, 70, 289–297.
doi:10.1002/dneu.20758
Chapman, S. B., Aslan, S., Spence, J. S., Dena, L. F.,
Keebler, M. W., Didehbani, N., & Lu, H. (2013).
Shorter term aerobic exercise improves brain, cogni-
tion, and cardiovascular tness in aging. Frontiers in
Aging Neuroscience, 5, 75.
Clarke, P. J., Nanthakumar, S., Notebaert, L., Holmes,
E. A., Blackwell, S. E., & MacLeod, C. (2014). Simply
imagining sunshine, lollipops and rainbows will not
budge the bias: e role of ambiguity in interpretive
bias modication. Cognitive erapy and Research,
38, 120–131.
Colcombe, S. J., Erickson, K. I., Scalf, P. E., Kim, J. S.,
Prakash, R., McAuley, E., . . . Kramer, A. F. (2006).
Aerobic exercise training increases brain volume in
aging humans. e Journals of Gerontology. Series A:
Biological Sciences and Medical Sciences, 61, 1166–
1170.
Connor, K. M., & Davidson, J. R. (2003). Development
of a new resilience scale: e Connor‐Davidson Re-
silience Scale (CD‐RISC). Depression and Anxiety,
18, 76–82.
Cotman, C. W., & Berchtold, N. C. (2002). Exercise: A
behavioral intervention to enhance brain health and
plasticity. Trends in Neurosciences, 25, 295–301.
Davidson, R. J., & Begley, S. (2012). e emotional life of
your brain. New York, NY: Plume.
Donnon, T., & Hammond, W. (2007). A psychometric
assessment of the self-reported Youth Resiliency:
Assessing Developmental Strengths questionnaire.
Psychological Reports, 100, 963–978.
Duckworth, A. L., Peterson, C., Matthews, M. D., &
Kelly, D. R. (2007). Grit: Perseverance and passion
for long-term goals. Journal of Personality and Social
INTERNATIONAL JOURNAL OF NEUROPSYCHOTHERAPY Volume 4 Issue 1 (2016)
43
Psychology, 92, 1087–1101.
Eckenrode, J. (1984). Impact of chronic and acute stress-
ors on daily reports of mood. Journal of Personality
and Social Psychology, 46, 907–918.
Edward, K. (2005). Resilience: A protector from depres-
sion. Journal of the AmericanPsychiatric Nurses Asso-
ciation, 11, 241–243. doi:10.1177/1078390305281177
Elisei, S., Sciarma, T., Verdolini, N., & Anastasi, S.
(2013). Resilience and depressive disorders (Supple-
mental material]. Psychiatria Danubina, 25, S263–
267.
Elliot, A. J., & Covington, M. V. (2001). Approach and
avoidance motivation. Educational Psychology Re-
view, 13, 73–92.
Elliot, A. J., & rash, T. M. (2002). Approach-avoid-
ance motivation in personality: Approach and avoid-
ance temperaments and goals. Journal of Personality
and Social Psychology, 82, 804–818.
Fredrickson, B. L., & Branigan, C. (2012, June). Posi-
tive emotions broaden the scope of attention and
thought‐action repertoires. Cognition and Emotion,
19. Retrieved from http://www.ncbi.nlm.nih.gov/
pmc/articles/PMC3156609/
Friborg, O., Hjemdal, O., Rosenvinge, J. H., & Marti-
nussen, M. (2003). A new rating scale for adult re-
silience: What are the central protective resources
behind healthy adjustment? International Journal of
Methods in Psychiatric Research, 12, 65–76.
Giese, M., Unternaehrer, E., Brand, S., Calabrese, P.,
Holsboer–Trachsler, E., & Eckert, A. (2013). e in-
terplay of stress and sleep impacts BDNF level. PloS
One, 8, e76050. doi:10.1371/journal.pone.0076050
Greer, S. M., Goldstein, A. N., & Walker, M. P. (2013,
August). e impact of sleep deprivation on food
desire in the human brain. Nature Communications,
4. Retrieved from http://www.nature.com/ncom-
ms/2013/130806/ncomms3259/full/ncomms3259.
html
Heernan, T. M. (2008). e impact of excessive alcohol
use on prospective memory: A brief review. Current
Drug Abuse Reviews, 1, 36–41.
Herrman, H., Stewart, D. E., Diaz-Granados, N., Berger,
E. L., Jackson, B., & Yuen, T. (2011). What is resil-
ience? Canadian Journal of Psychiatry, 56, 258–65
Hirshkowitz, M., Whiton, K., Albert, S. M., Alessi, C.,
Bruni, O., DonCarlos, L., . . . Hillard, P. J. (2015).
National Sleep Foundation’s sleep time duration rec-
ommendations: Methodology and results summary.
Sleep Health, 1, 40–43. doi:10.1016/j.sleh.2014.12.010
Hjemdal, O., Friborg, O., Stiles, T. C., Martinussen, M.,
& Rosenvinge, J. H. (2006). A new scale for adoles-
cent resilience: Grasping the central protective re-
sources behind healthy development. Measurement
and Evaluation in Counseling and Development, 39,
84–96.
Hurtes, K., & Allen, L. (2001). Measuring resiliency
in youth: e Resiliency Attitude and Skills Profile.
erapeutic Recreation Journal, 35, 333–347.
Hystad, S. W., Eid, J., Johnsen, B. H., Laberg, J. C., &
Bartone, P. T. (2010). Psychometric properties of the
revised Norwegian Dispositional Resilience (Hardi-
ness) Scale. Scandinavian Journal of Psychology, 51,
237–245. doi:10.1111/j.1467-9450.2009.00759.x
Issa, G., Wilson, C., Terry, A. V., Jr., & Pillai, A. (2010).
An inverse relationship between cortisol and BDNF
levels in schizophrenia: Data from human postmor-
tem and animal studies. Neurobiology of Disease, 39,
327–333. doi:10.1016/j.nbd.2010.04.017
Jackson, C. J., Hobman, E. V., Jimmieson, N. L., & Mar-
tin, R. (2009). Comparing dierent approach and
avoidance models of learning and personality in the
prediction of work, university, and leadership out-
comes. British Journal of Psychology, 100(2), 283–
312. doi:10.1348/000712608X322900.
Kandel, E. R. (1998). A new intellectual framework for
psychiatry. e American Journal of Psychiatry, 155,
457–469.
Kandel, E. R., Schwartz, J. H., Jessell, T. M. Siegelbaum,
S. A., & Hudspeth, A. J., (Eds.). (2013). Principles
of neural science (5th ed.). New York, NY: Mc-
Graw-Hill.
Killgore, W. D. S. (2010). Eects of sleep deprivation on
cognition. In G. A Kerkhof & H. P. A. van Dongen
(Eds.), Human Sleep and Cognition: Part 1: Basic Re-
search (pp. 105–130). Amsterdam, e Netherlands:
Elsevier.
Kleim, B., örn, H. A., & Ehlert, U. (2014). Positive
interpretation bias predicts well-being in medical
interns. Frontiers in Psychology, 5, 640. doi:10.3389/
fpsyg.2014.00640
44
INTERNATIONAL JOURNAL OF NEUROPSYCHOTHERAPY Volume 4 Issue 1 (2016)
Kong, F., Wang, X., Hu, S., & Liu, J. (2015). Neural
correlates of psychological resilience and their rela-
tion to life satisfaction in a sample of healthy young
adults. NeuroImage, 123, 165–172. doi:10.1016/j.
neuroimage.2015.08.020
Leahey, T. M., Kumar, R., Weinberg, B. M., & Wing,
R. R. (2012). Teammates and social inuence aect
weight loss outcomes in a team‐based weight loss
competition. Obesity, 20, 1413–1418. doi:10.1038/
oby.2012.18
Leahey, T. M., LaRose, G. J., Fava, J. L., & Wing, R. R.
(2011). Social inuences are associated with BMI
and weight loss intentions in young adults. Obesity,
19, 1157–1162. doi:10.1038/oby.2010.301
Lu, B., Nagappan, G., Guan, X., Nathan, P. J., & Wren,
P. (2013). BDNF-based synaptic repair as a dis-
ease-modifying strategy for neurodegenerative dis-
eases. Nature Reviews Neuroscience, 14, 401–416.
doi:10.1038/nrn3505
Mäntyselkä, P. T., Turunen, J. H., Ahonen, R. S., & Kum-
pusalo, E. A. (2003). Chronic pain and poor self-rat-
ed health. JAMA, 290(18), 2435–2442.
Masten, A. S., Cutuli, J. J., Herbers, J. E., & Reed, M. G.
(2009). Resilience in Development. In C. R. Snyder
& S. J. Lopez (Eds.), e handbook of positive psychol-
ogy (pp. 117–131). New York, NY: Oxford University
Press.
McWilliams, L. A., Cox, B. J., & Enns, M. W. (2003).
Mood and anxiety disorders associated with chronic
pain: an examination in a nationally representative
sample. Pain, 106, 127– 133.
Min, J. A., Yoon, S., Lee, C. U., Chae, J. H., Lee, C., Song,
K. Y., & Kim, T. S. (2013). Psychological resilience
contributes to low emotional distress in cancer pa-
tients. Supportive Care in Cancer, 21, 2469–2476.
doi:10.1007/s00520-013-1807-6
Molteni, R., Barnard, R. J., Ying, Z., Roberts, C. K., &
Gomez-Pinilla, F. (2002). A high-fat, rened sug-
ar diet reduces hippocampal brain-derived neuro-
trophic factor, neuronal plasticity, and learning. Neu-
roscience, 112, 803–814.
Oettingen, G., & Wadden, T. A. (1991). Expectation,
fantasy, and weight loss: Is the impact of positive
thinking always positive? Cognitive erapy and Re-
search, 15, 167–175.
Olsson, C. A., Bond, L., Burns, J. M., Vella-Brodrick, D.
A., & Sawyer, S. M. (2003). Adolescent resilience: A
concept analysis. Journal of Adolescence, 26, 1–11.
Oshio, A., Kaneko, H., Nagamine, S., & Nakaya, M.
(2003). Construct validity of the Adolescent Resil-
ience Scale. Psychological Reports, 93, 1217–1222.
Peterson, B. S., Wang, Z., Horga, G., Warner, V., Ruth-
erford, B., Klahr, K. W., . . . Weissman, M. M. (2014).
Discriminating risk and resilience endophenotypes
from lifetime illness eects in familial major de-
pressive disorder. JAMA Psychiatry, 71, 136–148.
doi:10.1001/jamapsychiatry.2013.4048
Preston, A. R., & Eichenbaum, H. (2013). Interplay
of hippocampus and prefrontal cortex in memo-
ry. Current Biology, 23, R764–773. doi:10.1016/j.
cub.2013.05.041
Pujol, J., Harrison, B. J., Ortiz, H., Deus, J., Soriano-Mas,
C., Lopez-Sola, M., . . . Cardoner, N. (2009). Inu-
ence of the fusiform gyrus on amygdala response
to emotional faces in the non-clinical range of so-
cial anxiety. Psychological Medicine, 39, 1177–1187.
doi:10.1017/S003329170800500X
Rossouw, P. (2015, March/May). Resilience: A
neurobiological perspective. Neuropsychotherapy in
Australia, 31, 3–8.
Russo, S. J., Murrough, J. W., Han, M. H., Charney, D.
S., & Nestler, E. J. (2012). Neurobiology of resilience.
Nature Neuroscience, 15, 1475–1484. doi:10.1038/
nn.3234
Rutter, M. (1985). Resilience in the face of adversity.
Protective factors and resistance to psychiatric dis-
order. e British Journal of Psychiatry, 147, 598–611.
Rutter, M. (2012). Resilience as a dynamic concept.
Development and Psychopathology, 24, 335–344.
doi:10.1017/S0954579412000028
Schore, A. N. (2000). Attachment and the regulation of
the right brain. Attachment & Human Development,
2, 23–47.
Simon, G. E., Ludman, E. J., Linde, J. A., Operskalski, B.
H., Ichikawa, L., Rohde, P., . . . Jeery, R. W. (2008).
Association between obesity and depression in mid-
dle-aged women. General Hospital Psychiatry, 30,
32–39. doi:10.1016/j.genhosppsych.2007.09.001
Smith, B. W., Dalen, J., Wiggins, K., Tooley, E., Chris-
topher, P., & Bernard, J. (2008). e Brief Resilience
INTERNATIONAL JOURNAL OF NEUROPSYCHOTHERAPY Volume 4 Issue 1 (2016)
45
Scale: Assessing the ability to bounce back. Interna-
tional Journal of Behavioral Medicine, 15, 194–200.
doi:10.1080/10705500802222972
Stewart, D., Sun, J., Patterson, C., Lemerle, K., & Har-
die, M. (2004). Promoting and building resilience
in primary school communities: Evidence from a
comprehensive ‘health promoting school’ approach.
International Journal of Mental Health Promotion, 6,
26–33. doi:10.1080/14623730.2004.9721936
Svanberg, P. O. G. (1998). Attachment, resilience and
prevention. Journal of Mental Health, 7, 543–578.
doi:10.1080/09638239817716
Tugade, M. M., Fredrickson, B. L., & Barrett, L. F. (2004).
Psychological resilience and positive emotional
granularity: Examining the benets of positive emo-
tions on coping and health. Journal of Personality, 72,
1161–1190. doi:10.1111/j.1467-6494.2004.00294.x
Ungar, M., & Liebenberg, L. (2011). Assessing resil-
ience across cultures using mixed methods: Con-
struction of the Child and Youth Resilience Mea-
sure. Journal of Mixed Methods Research, 5, 126–149.
doi:10.1177/1558689811400607
Wagnild, G. M., & Young, H. M. (1993). Development
and psychometric evaluation of the Resilience Scale.
Journal of Nursing Measurement, 1, 165–178.
Wethington, E., & Kessler, R. C. (1986). Perceived sup-
port, received support, and adjustment to stressful
life events. Journal of Health and Social Behavior, 27,
78–89.
Windle, G., Bennett, K. M., & Noyes, J. (2011). A meth-
odological review of resilience measurement scales.
Health and Quality of Life Outcomes, 9, 1–18.
Windle, G., Markland, D. A., & Woods, R. T. (2008).
Examination of a theoretical model of psychological
resilience in older age. Aging and Mental Health, 12,
285–292. doi:10.1080/13607860802120763
World Bank. (2014, April). Out of the shadows: Making
mental health a global development priority. Meeting
co-hosted by the World Bank and the World Health
Organization, Washington, DC. Retrieved from
http://www.who.int/mental_health/WB_WHO_
meeting_2016.pdf?ua=1
World Health Organisation. (2015). Mental Health At-
las 2014. Retrieved from http://apps.who.int/iris/
bitstream/10665/178879/1/9789241565011_eng.pd-
f?ua=1&ua=1