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The Predictive 6-Factor Resilience Scale: Neurobiological Fundamentals and Organizational Application


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Psychological resilience is currently viewed as being primarily a mental construct, with few measurement scales explicitly considering health hygiene factors as an integral component that facilitates healthy adaption to adversity. Ongoing research has provided greater clarity on the neurobiological nature of psychological resilience, suggesting that health hygiene factors affect mental wellbeing on a neurobiological basis. Objective: We describe the neurobiological fundamentals of a brief psychological resilience rating scale called the Predictive 6 Factor Resilience Scale (PR6) consisting of 16 items. Using the PR6, we test the hypothesis that health hygiene factors correlate with psychological resilience domains. In addition, we measure forward-looking elements to contrast with point-in-time measurements and check for consistency with the resilience construct. Methods: An existing neurobiological model was used as the basis for PR6 resilience domains which was then compared to other resilience scales for similarity in domain coverage. The 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, along with correlation between health hygiene factors and current resilience domains. Differences in resilience between industry, gender, and age groups were considered. Results: PR6 resilience scores showed good internal consistency over 16 items and, alongside correlation studies, confirmed that health hygiene factors have a statistically significant 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. Conclusions: We conclude 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 favourably impact healthy adaptation to difficult circumstances and stress management. The foundations of each resilience domain measured by the PR6 provides for targeted treatment to improve holistic resilience capacity, and industry application in this study shows efficacy for both point-in-time and forward looking psychological resilience assessment.
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The Predictive 6-Factor Resilience Scale:
Neurobiological Fundamentals and Organizational Application
Pieter J. Rossouw and Jurie G. Rossouw
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 aect 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. Dierences 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, conrmed that health hygiene factors have a statistically
signicant 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 dicult 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 ecacy for both point-in-time and forward-looking psychological resil-
ience assessment.
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
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:
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:
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). Briey, 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 dierences, indicating the impor-
tance of accurately measuring variances within groups
for ecacious 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 eects of positive emotion
might together account for the salutary eects 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 condence 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
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.
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 inuenced 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 aect 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 inuence 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
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 Prole; DRS = Dispositional Resilience Scale; YRADS = Youth Resiliency: Assessing Devel-
opmental Strengths; CYRM = Child and Youth Resilience Measure; CHKS = California Healthy Kids Survey.
*Existential aloneness.
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 dierences 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-ecacy 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
Prole (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), reecting 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
identied 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 reects 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 eectively 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 eect and the undoing eect (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 Eect 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 Davidsons
model presents clear alignment and points to the abil-
ity of the PFC to eectively 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-
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 eectively regulate limbic functions is supported by
strategies such as interpretation bias, which has been
shown to have a protective eect 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, reecting 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 aect 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 inuences aect 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,
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 eect 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 aecting 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 eect of BDNF on resilience and nd three physio-
logical factors that aect 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 (Heernan, 2008; Molteni, Barnard, Ying,
Roberts, & Gomez-Pinilla, 2002). More generally, the
psychological link between the broader inuence 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
conict 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 specic
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
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 oered to the organization in the
form of an online device completed condentially 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
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.
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 conrmed with an Anderson–Darling
test of 0.440 and a p-value of 0.289 for the full popula-
tion. Floor and ceiling eects were not encountered as
no responses reached the lowest level, while only one
response reached near the upper bound with a score of
Group Analysis
Table 3 summarises scores for the dierent 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 signicant dierence, while Education and Not
Specied scores at the time of measurement did not
have sucient data to draw meaningful conclusions.
Similar results were observed within Age, Gender, and
Location whereas once a sucient number of responses
had been received, no statistically signicant dierenc-
es were noted within groups for overall scores. Domain
analysis indicated one statistically signicant dierence
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
dierence was not statistically signicant (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 signicance can be validated.
Figure 3 shows gender dierences by domain of resil-
ience. is analysis indicated an area of statistically sig-
nicant dierence 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 specied 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 specied 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 specied 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
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 dierences noted in the
Tenacity and Reasoning domains indicate statistical sig-
nicance 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 conrm the relationship through
Cronbach’s alpha.
Item analysis yielded a Cronbachs 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 eect 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 signicantly: Exer-
cise frequency (Item 15) had the strongest eect (a =
0.719 if omitted); adherence to healthy nutrition (Item
16) had the second strongest eect (a = 0.7295 if omit-
ted); and general perceptions about health (Item 13) had
the third strongest eect (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 eect on alpha, with Item 6
(reverse scored) and Item 12 reducing alpha to 0.7251
and 0.7173 if omitted. No signicant dierences were
Figure 2. Overall resilience scores per gender and age group.
Note. 1n = 13, 2n = 2, 3n = 12.
Figure 3. Domain scores per gender.
found in Momentum scores between Industry, Gender,
or Age groupings.
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
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.
and Finance industries, rst, to validate the hypothesis
and, second, to investigate its potential for application
among individuals and in the workplace.
Statistically signicant 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 conrm that the PR6 represents a val-
id psychological resilience measurement tool. e PR6
unies 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 specic resilience factors.
e diverse industries of Healthcare and Finance dis-
played no statistically signicant dierences in overall
PR6 scores although some dierences were noted on a
domain level—signicantly 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 eect on the overall resilience
construct further bolsters a holistic resilience treatment
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. Reecting 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 signicant deviation, allowing for multiple
modes of delivery.
In consideration of dierences 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 specic training
through their professional education. Dierences found
in the Health domain, particularly the lower scores in
Finance, are suspected to be largely related to gender
dierences given that a high percentage of the Health-
care group was female, and female participants overall
had higher Health scores than males.
e signicantly lower Health scores for males, ac-
companied by slightly higher (though not signicant)
scores in Tenacity and Reasoning, suggest that males
may sacrice 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-
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 eects
of chronic sleep disturbance are well documented and
are expected to have an eect on long-term well-being.
Regarding the second item, resilience oen 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 dierent
versions of these items in order to further investigate
and rene 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 eective
methods of resilience modication, 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 specic 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 eective treatment to im-
prove overall resilience and well-being by focusing on
individual areas as highlighted through the PR6.
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... Braun and Clarke's [48] framework for qualitative thematic analysis guided the inductive analysis protocol. Deductive analysis was guided by a coding structure generated using resilience themes drawn from both the Predictive 6-Factor Resilience Scale (PR-6) [49,50] and the Resilience & Core Character Competencies Framework [51]. Once the coding structure was developed, a first round of coding was completed for all data. ...
... Resilience Characteristics. Resilience characteristics isolated from the written entries of study participants reflected resilience characteristics found in the literature including post-traumatic growth, adaptability, emotional/social connectedness, composure, and reasoning [33,49,50,52,53]. These are described below. ...
... Vision, composure, tenacity, reasoning, collaboration and health, all components of resilience included in the PR-6 [49,50], were also evident in the women's EW entries. While study participants wrote of feeling overwhelmed during the evacuation, they maintained composure for the sake of their children and the health of their unborn child. ...
The worst disaster of natural origin in recent Canadian history occurred in May 2016 in the northern Alberta community of Fort McMurray Wood Buffalo (FMWB). Among the 88,000 people abruptly evacuated amidst a raging wildfire were approximately 1850 pregnant or pre-conception women. Based on the Allostatic Load and Preterm Birth Conceptual Framework (Olson et al., 2015) [1], a simple, cost-effective expressive writing intervention following Pennebaker's work (Pennebaker and Beall, 1986; Pennebaker et al., 2007) [2,3] was implemented in a primary study to help mitigate the negative effects of stress on a sample of these women and their unborn children. Journal writing served as an intervention in the primary study while the contents of the journal entries became the data analyzed in this qualitative study. This study utilized both inductive and deductive thematic analysis of journal entries completed by 54 women over four consecutive days (15 min/day). Deductive analysis followed a coding structure that was generated from two resilience scales. Themes that emerged during inductive analysis were also coded. The main themes that emerged described the women's challenging experiences: fears for themselves and their offspring, fire-related and past trauma, and relationship changes. Resilience characteristics and practices also emerged from the writings and mirrored those found in the literature: (a) post-traumatic growth, (b) adaptability, (c) emotional/social connectedness, (d) composure, and (e) reasoning. This paper highlights the challenging experiences of pregnant women exposed to a disaster and the resilience they demonstrated in the face of the tragedy.
... Eudaimonic well-being (autonomy, environmental mastery, personal growth, purpose in life, positive relations with others, and self-acceptance [Ryff, 1989;Ryff & Keyes, 1995;Ryff, 2014]) emerges from natural processes, through underlying genetic and neural substrates (Archontaki et al., 2013;Lewis et al., 2014), and acts as a protective resilient factor across life-span transitions (Ryff, 2014). Finally, there are health systems, again reflecting a broaden-and-build theory, in which there is a reciprocal relationship between trait resilience and positive health functioning through the promotion of feeling able to deal with adverse health situations (Fredrickson & Branigan, 2005;Rossouw & Rossouw, 2016). ...
... We also included a number of personality, intelligence, cognitive, and health and well-being factors to consider proxy accounts of resilience as reflecting (i) the resilient personality (Asendorpf & van Aken, 1999;Robins et al., 1996), (ii) successful cognitive functioning through the theory of resilience functioning (Cicchetti & Curtis, 2006) and the cognitive model of psychological resilience (Parsons et al., 2016), (iii) the broaden-and-build theory of resilience reflecting successful emotional and health organisation (Kay, 2016;Troy & Mauss, 2011;Fredrickson & Branigan, 2005;Rossouw & Rossouw, 2016), and (iv) eudaimonic well-being as a protective resilience factor (Ryff, 2014). ...
... To consider health and emotional processes that are thought to represent resilience through the successful management and regulation of emotional and health systems (Kay, 2016;Troy & Mauss, 2011;Fredrickson & Branigan, 2005;Rossouw & Rossouw, 2016), we administered three questionnaires that represent successful management and regulation of these two systems. The first was the Physical Health Questionnaire (Schat et al., 2005). ...
The current paper establishes the latent factors of many direct or proxy trait resilience assessments. Study 1 (n=849) demonstrates four latent factors (recovery, sustainability, adaptability, and social cohesion) among 61 direct and proxy assessments of resilience. Three of these four factors are best described within a three-factor model of ecological resilience, with an additional social-orientated resilience factor. Study 2 (n=340) replicates the factors using indicators of the factors found in Study 1. A bifactor model of the four factors provides the best fit of the data, with measurement invariance across broad groups for gender, age, and ethnicity. The findings suggest a ‘mixed model’ of resilience summarising over 30 years of research using direct and proxy assessments of resilience.
... It has been proposed that individuals who possesses high standards, tenacity, trust in one's instincts, the ability to tolerate negative affect, the ability to adapt to changing circumstances, and acceptance of oneself and one's life situation are more likely to positively adapt to stress and adversity [19]. Feelings of personal competence, [19,22] engagement in self-leadership, [78] social skills, [22,84], and the ability to engage in behaviors that promote health and well-being have also been highlighted as predictive of positive stress coping [85]. Additionally, "hardiness" [83] or "personal hardiness" [86], as defined as an individual's "courage and motivation to face stressors accurately (rather than to deny or catastrophize them)" [87], has been considered as a pathway to resilience by way of an individual approaching, rather than avoiding, existing stressors and engaging in problem-solving and seeking out encouragement and assistance from others. ...
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Psychological resilience is an important construct that can enhance athletic performance and foster valuable life skills. Through positive adaptation to adversity and stressors in the athletic arena, athletes are able to cultivate their ability to effectively respond to negative stimuli, ultimately evolving to personal growth. For young female athletes, development of resilience may be particularly important. Young female athletes face distinct challenges in sport including sport inequity, body image issues, eating disorders, increased mental distress, and internalization of emotions. The aim of this review is to define and describe the construct of resilience and discuss the implications and applications relevant to young female athletes. By understanding how to foster resilience strategies in this population, we can enhance sport performance and enjoyment, as well as bolster valuable life skills that facilitate personal growth.
... The control subscale is the most common construct in 21 resilience scales [7] and studies have postulated a convergence between emotional regulation and the concept of control. For example, the composure domain from the Predictive 6-factor Resilience Scale (P6RS) is primarily about emotional regulation and the ability to recognize, understand, and act on internal prompts and physical signals [37]. Some of the items in the Adolescent Resilience Scale which are "I can stay calm in hard circumstances" and a negative item 'I have difficulty in controlling my anger' represent emotional regulation [38]. ...
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Purpose Most of the resilience scales were developed for the non-medical population, therefore the purpose of this study was developing and validating a resilience scale for medical professionals – namely Medical Professionals Resilience Scale (MeRS). Methods A questionnaire development and validation study was conducted. The resilience domains and items were identified and generated through a literature review. The content validation was carried out by content experts and the content validity index (CVI) was calculated. The face validation was performed by medical officers and the face validity index (FVI) was calculated. The final MeRS was administered to 167 medical officers, exploratory factor analysis (EFA) and reliability analysis were performed to assess MeRS’s factorial structure and internal consistency. Results Four domains with 89 items of medical professionals’ resilience were developed. Following that, the content and face validation was conducted, and a total of 41-items remained for construct validation. EFA extracted four factors, namely growth, control, involvement, and resourceful, with a total of 37 items. The items’ CVI and FVI values were more than 0.80. The final MeRS’s items had factor loading values ranged from 0.41 to 0.76, and the Cronbach’s alpha values of the resilience domains ranged from 0.72 to 0.89. Conclusions MeRS is a promising scale for measuring medical professionals’ resilience as it showed good psychometric properties. This study provided validity evidence in terms of content, response process, and internal structure that supported the validity of MeRS in the measurement of resilience domains among medical professionals.
... The control subscale is the most common construct in 21 resilience scales [7] and studies have postulated a convergence between emotional regulation and the concept of control. For example, the composure domain from the Predictive 6-factor Resilience Scale (P6RS) is primarily about emotional regulation and the ability to recognize, understand, and act on internal prompts and physical signals [37]. Some of the items in the Adolescent Resilience Scale which are "I can stay calm in hard circumstances" and a negative item 'I have difficulty in controlling my anger' represent emotional regulation [38]. ...
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Purpose: Most of the resilience scales were developed for the non-medical population, therefore the purpose of this study was developing and validating a resilience scale for medical professionals – namely Medical Professionals Resilience Scale (MeRS). Methods: A questionnaire development and validation study was conducted. The resilience domains and items were identified and generated through a literature review. The content validation was carried out by content experts and the content validity index (CVI) was calculated. The face validation was performed by medical officers and the face validity index (FVI) was calculated. The final MeRS was administered to 167 medical officers, exploratory factor analysis (EFA) and reliability analysis were performed to assess MeRS’s factorial structure and internal consistency. Results: Four domains with 89 items of medical professionals’ resilience were developed. Following that, the content and face validation was conducted, and a total of 41-items remained for construct validation. EFA extracted four factors, namely growth, control, involvement, and resourceful, with a total of 37 items. The items’ CVI and FVI values were more than 0.80. The final MeRS’s items had factor loading values ranged from 0.41 to 0.76, and the Cronbach’s alpha values of the resilience domains ranged from 0.72 to 0.89. Conclusion: MeRS is a promising scale for measuring medical professionals’ resilience as it showed good psychometric properties. This study provided validity evidence in terms of content, response process, and internal structure that supported the validity of MeRS in the measurement of resilience domains among medical professionals.
... Our previous research 56 68,69 . Collectively this provides evidence for the necessity to maintain a physiologically healthy lifestyle in order to provide an optimal environment for plasticity to take place. ...
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Background Digital interventions hold promise to address the global decline in mental health. Resilience is indicated as an avenue to enact preventative care. Combining resilience enhancement with a neuroscience-based learning technique may attenuate current trends. Objective This study sets out the neurobiological mechanics of small, micro-session learning (microtasks), and tested their efficacy in building resilience capacity through a digital conversive program called Driven to create lasting behavioural change. Methods Using the foundations of the microtask approach, Driven was constructed as an automated intervention to improve resilience capacity, based on the PR6 resilience framework. Real world data from a sub-clinical cohort (n=387) across four organisations were analysed using the PR6 resilience psychometric to assess resilience pre and post intervention. Usage rates of Driven and other factors were investigated through regression analyses as predictors of future resilience capacity improvement. Results Of the invited cohort, 89% (n=345/387) participated and were mostly male (74.5%, n=257/345). Median time between first and second PR6 assessment was 199 days. Of participants, 70.4% (n=245/345) completed the second assessment. Average individual improvement in resilience was 10.9% for the remeasured cohort (n=245). Results showed higher daily usage of Driven resulted in greater resilience improvements, with usage of more than once every four days resulted in a 15.6% improvement, and average usage once every two days resulted in a 24.9% improvement. Low or no usage of Driven showed no significant improvement. Further, a lower pre intervention score resulted in higher participation and higher subsequent improvement. Conclusion Delivering microtasks through a digital virtual coaching approach presents a reliable method to achieve lasting behavioural change and improve resilience capacity. Additionally, Driven displays an ability to provide effective preventative intervention to those with greater need.
The COVID‐19 pandemic has had a significant impact on people's lives, requiring a shift in focus to short‐term survival and management of changes in relationships, academic and work environments, and future career options. Understandably, one of the most seminal aspects of career development—deciding on a future career—can seem overwhelming or even irrelevant in the face of such challenges. Neuroscience research offers a scientifically grounded framework for understanding the impact of chronic acute stressors, such as COVID‐19, on functioning and can provide direction for interventions that foster resilience and support clients' ability to reengage in career decision‐making. We discuss research related to the neuroscience of stress and resilience and ways to apply that information within career counseling.
The reintegration process is not a simple one. There are many papers about the difficulties of re-entry into society and the possible reasons of the success or the failure of reintegration. In this article, I am going to write about the role of resilience in prisoners’ reintegration process. In a brief presentation of the concept of resilience, I will introduce the models of resilience and the role of protective factors. From the several instruments that can be used to measure resilience I will highlight the most common and most empirically based scales that can be a great help to identify protective factors of incarcerated people, to make the reintegration processes more successful.
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Extensive research on humans suggests that exercise could have benefits for overall health and cognitive function, particularly in later life. Recent studies using animal models have been directed towards understanding the neurobiological bases of these benefits. It is now clear that voluntary exercise can increase levels of brain-derived neurotrophic factor (BDNF) and other growth factors, stimulate neurogenesis, increase resistance to brain insult and improve learning and mental performance. Recently, high-density oligonucleotide microarray analysis has demonstrated that, in addition to increasing levels of BDNF, exercise mobilizes gene expression profiles that would be predicted to benefit brain plasticity processes. Thus, exercise could provide a simple means to maintain brain function and promote brain plasticity.
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Introduction: There is considerable variability in the response of individuals to adverse environmental conditions, while some develop psychiatric illnesses like depression, others seem very capable of dealing with it. It is in this observation that the concepts of vulnerability and resilience are rooted. Methods: We conducted a review of the literature by inserting in PubMed the keywords resilience, vulnerability and depressive disorders. Discussion and conclusions: Freud formerly used the so-called crystal-principle to describe the concept of vulnerability: according to this, the different psychopathologies would arise depending on the different psychological weaknesses, just like a crystal thrown to the ground shatters along its lines of cleavage intrinsic to it, albeit invisible. The term resilience has been borrowed from physics where it is used to describe the ability of a material to withstand impact without cracking. In psychology, the term resilience refers to a complex and dynamic multidimensional construct, which derives from the interaction of neurobiological, social and personal factors and indicates the ability to adaptively cope with stress and adversity, preserving a normal physical and psychological functioning. Resilience has proven to be a protective factor against the development of psychiatric disorders such as depression. Making a conceptual leap, the concepts of vulnerability and resilience can be related to the psychodynamic classification of depression postulated by Gaetano Benedetti, who distinguished four kinds of depression: the first due to the failure of the ego, the second to the perversion of the superego, the third to the inhibition of the Id and the fourth to the collapse of the ego ideal. It is possible to improve the resilience of depressed subjects through pharmacological and psychotherapeutic interventions.
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Resilience is defined as an individual's capacity to effectively respond and adapt to stress and adversity (APA 2014). Stress and adversity can present in a multitude of situations on all levels – biological, emotional, psychological, social or spiritual. Traditionally resilience has been viewed as a capacity that is learned through behaviour, developed over time (Boyden & Mann 2005) and is linked to a cultural adaptation process (Dawes & Donald 2000; Castro & Murray 2010), and risk factors have been identified that compromise resilience (Boyden & Mann 2005). Resilience is closely aligned with emotional wellness (Ungar 2004) and a capacity to endure and achieve long term goals (Duckworth 2007). Until recently very few research studies have been conducted focusing on the biological markers of resilience – especially in the domain (context?) of the neural basis of emotional styles and resilience. One of the pioneers in this field is Richard Davidson. His research led to the development of various dimensions of emotional style linked to neurobiological markers that assist with a better understanding of the neuroscience of resilience. This article explores resilience from neurobiological perspective.
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Cognitive theories of emotion posit that affective responses may be shaped by how individuals interpret emotion-eliciting situations. This study tested whether individual differences in interpretation bias (i.e., interpreting ambiguous scenarios in a more negative or positive manner) independently predict trait resilience and depression in medical interns. Interpretation bias and trait resilience scores were assessed in 47 interns prior to their first internship. Depressive symptoms were assessed twice during internship. Nearly half of the sample (42%) scored above the cut-off for mild depressive symptoms during internship, a significant rise compared to the initial assessment. Those with a more positive interpretation bias had higher trait resilience (β = 0.44, p = 0.004) and a 6-fold decreased depressive symptom risk during internship (OR = 6.41, p = 0.027). The predictive power of a positive interpretation bias for decreased depression symptoms held over and above initial depressive symptoms, demographics and trait reappraisal. Assessing positive interpretation bias may have practical utility for predicting future well-being in at risk-populations.
Resilience in human development is defined in relation to positive adaptation in the context of significant adversity, emphasizing a developmental systems approach. A brief history and glossary on the central concepts of resilience research in developmental science are provided, and the fundamental models and strategies guiding the research are described. Major findings of the first four decades of research are summarized in terms of protective and promotive factors consistently associated with resilience in diverse situations and populations of young people. These factors-such as self-regulation skills, good parenting, community resources, and effective schools- suggest that resilience arises from ordinary protective processes, common but powerful, that protect human development under diverse conditions. The greatest threats posed to children may be adversities that damage or undermine these basic human protective systems. Implications of these findings for theory and practice are discussed, highlighting three strategies of fostering resilience, focused on reducing risk, building strengths or assets, and mobilizing adaptive systems that protect and restore positive human development. The concluding section outlines future directions of resilience research and its applications, including rapidly growing efforts to integrate research and prevention efforts across disciplines, from genetics to ecology, and across level of analysis, from molecules to media.
Resources that protect against the development of psychiatric disturbances are reported to be a significant force behind healthy adjustment to life stresses, rather than the absence of risk factors. In this paper a new scale for measuring the presence of protective resources that promote adult resilience is validated. The preliminary version of the scale consisted of 45 items covering five dimensions: personal competence, social competence, family coherence, social support and personal structure. The Resilience Scale for Adults (RSA), the Sense of Coherence scale (SOC) and the Hopkins Symptom Checklist (HSCL) were given to 59 patients once, and to 276 normal controls twice, separated by four months. The factor structure was replicated. The respective dimensions had Cronbach's alphas of 0.90, 0.83, 0.87, 0.83 and 0.67, and four-month test-retest correlations of 0.79, 0.84, 0.77, 0.69 and 0.74. Construct validity was supported by positive correlations with SOC and negative correlations with HSCL. The RSA differentiated between patients and healthy control subjects. Discriminant validity was indicated by differential positive correlations between RSA subscales and SOC. The RSA-scale might be used as a valid and reliable measurement in health and clinical psychology to assess the presence of protective factors important to regain and maintain mental health. Copyright
Objective: The objective was to conduct a scientifically rigorous update to the National Sleep Foundation's sleep duration recommendations. Methods: The National Sleep Foundation convened an 18-member multidisciplinary expert panel, representing 12 stakeholder organizations, to evaluate scientific literature concerning sleep duration recommendations. We determined expert recommendations for sufficient sleep durations across the lifespan using the RAND/UCLA Appropriateness Method. Results: The panel agreed that, for healthy individuals with normal sleep, the appropriate sleep duration for newborns is between 14 and 17 hours, infants between 12 and 15 hours, toddlers between 11 and 14 hours, preschoolers between 10 and 13 hours, and school-aged children between 9 and 11 hours. For teenagers, 8 to 10 hours was considered appropriate, 7 to 9 hours for young adults and adults, and 7 to 8 hours of sleep for older adults. Conclusions: Sufficient sleep duration requirements vary across the lifespan and from person to person. The recommendations reported here represent guidelines for healthy individuals and those not suffering from a sleep disorder. Sleep durations outside the recommended range may be appropriate, but deviating far from the normal range is rare. Individuals who habitually sleep outside the normal range may be exhibiting signs or symptoms of serious health problems or, if done volitionally, may be compromising their health and well-being.