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Risk Factors as Major Determinants of Resilience: A Replication Study
Yohanan Eshel, Shaul Kimhi, Mooli Lahad, Dmitry Leykin, Marina Goroshit
Tel Hai College, Israel
Resubmitted to Community Mental Health Journal
February 2018
Running head: Risk factors and resilience
Correspondence: Yohanan Eshel Ph.D. Department of Psychology,
Tel Hai College, Phone: 97248181625, E-mail: yeshel@psy.haifa.ac.il
Shaul Kimhi Ph.D. Department of Psychology, Tel Hai College,
Phone: 97248181623, E-mail: shaulkim@adm.telhai.ac.il
Mooli Lahad Ph.D. Department of Psychology, Tel Hai College,
Phone: 9720528455005, E-mail: lahadm@013net.net
Dmitry Leykin Ph.D. Department of Psychology, Tel Hai College,
Phone: 9720545901647, E-mail: dimleyk@gmail.com
Marina Goroshit Ph.D. Department of Psychology, Tel Hai College,
Phone: 9720546827850, E-mail: marina.and.mark@gmail.com
2 Risk factors and resilience
Abstract
Background and objectives. The present study was conducted in the context
of current concerns about replication in psychological research. It claims that risk
factors should be regarded as an integral part of the definition of individual resilience,
which should be defined in terms of the balance between individual strength or
protective factors, and individual vulnerability or risk factors (IND-SVR). Design.
Five independent samples, including 3457 Israeli participants, were employed to
determine the effects of resilience promoting and resilience suppressing variables on
the IND-SVR index of resilience, and on its two components: recovery from
adversity, and distress symptoms. Methods. Five path analyses were employed for
determining the role of distress symptoms as a measure of psychological resilience, as
compared to other indices of this resilience. Results. Results indicated the major role
of risk factors (distress symptoms) as an integral component of resilience. This role
was generally replicated in the five investigated samples. Conclusion. Risk factors
are legitimate, valid, and useful parts of the definition of psychological resilience.
Resilience research has shifted away from studying individual risk factors to
investigating the process through which individuals overcome the hardships they
experience. The present data seem to suggest that this shift should be reexamined.
Keywords: Resilience, distress symptoms, recovery from adversity, war, terror
3 Risk factors and resilience
Individual Resilience – Theoretical Framework
The present study investigates the role of risk factors as essential (negative)
components of resilience. It examines the hypothesis that risk factors as well as
protective factors constitute fundamental components of individual resilience, and
both of them will be validated by resilience supporting and resilience reducing
attributes. Furthermore, it is hypothesized that these associations will be replicated in
five independent large scale Israeli studies.
Theoretical analyses of resilience seem to be divided by the issue whether
resilience should be determined mainly by overcoming risk factors and lowered level
of distress symptoms (e.g., Bonanno, Rennick & Dekel, 2005; Hadi, Llabre, &
Spitzer, 2006), or by individual post adversity strength. Luthar, Cicchetti and Becker,
(2000) have observed that the focus of resilience research has shifted lately away
from studying risk factors, to understanding the process through which individuals
overcome the adversities they experience. Recent analyses of resilience tend to
preclude risk factors from the definition of resilience and to characterize it mainly by
protective elements which enhance individual strength. Resilience has thus been
defined as "the potential of manifested capacity of a dynamic system to adapt
successfully to disturbances that threaten the function, survival, or development of the
system" (Masten, 2015, p. 187), or as a stable trajectory of healthy functioning after a
highly adverse event (Southwick, Bonanno, Masten, Panter-Brick, & Yehuda, 2014).
A recent salutogenic model of coping with potential mass trauma (Braun-
Lewensohn, 2015) has thus described the entire coping process in terms of cognitive
resources, such as education and wisdom, and emotional resources based on dynamic
and flexible inner self. A different recent theorizing as well as accumulated Israeli
4 Risk factors and resilience
data (Eshel, 2016; Eshel & Kimhi, 2015a, 2016; Eshel, Kimhi, & Goroshit, 2016)
strongly support the contention that individual resilience is contingent concurrently on
gathering strength for thriving in face of external adversities, and on overcoming
internal risk factors. We have contended (Kimhi & Eshel, 2015) that determining
resilience by individual strengths, without simultaneously considering risk factors,
such as worries, concerns, or fears, may result in inaccurate and biased assessments of
this resilience. Resilience has thus been defined as the balance of individual strength
(protective factors) and vulnerability (risk factors) following an adversity or a
traumatic event (Eshel & Kimhi, 2016; Eshel, Kimhi, Lahad, & Leykin, 2016).
Luthar (1991) has claimed that resilient individual may be troubled by
distressing emotions and still show successful coping, regardless of these emotions.
We submit that most people experience some strength in face of adversity as well as
uncertainty and worries. The conflict between vigor and frailty, that is, between
positive and negative components of resilience, is a crucial part of the process of post
adversity readjustment. Successful coping with hardships and traumas represents a
solution of this conflict in which post-adversity strengths successfully counter distress
symptoms, whereas a level of vulnerability which is higher than post-adversity
strengths will often result in poor adaptation.
This analysis agrees with the contention that the benchmark of resilient behavior
under stress is defined by maintaining competent functioning despite interfering
emotionality (Garmezi, 1991). It echoes as well Charles (2010) and Masten (2011)
positions that resilience represents an integration of strength and vulnerability, and
that understanding adaptation to adversities requires a concurrent examination of
protective processes and risk factors. The importance of the interaction between
threats and resources in the face of a stressful encounter has been elaborated by
5 Risk factors and resilience
Lazarus and Folkman's (1984) distinction between primary and secondary cognitive
appraisals.
The dual nature of individual resilience has been investigated by several Israeli
studies which have used the post-adversity strength to vulnerability ratio (IND-SVR).
These studies demonstrated that this is a valid index of resilience which represents
concurrently recovery resources and the level of individual risk factors which may
obstruct this recovery (e.g., Eshel, 2016; Eshel & Kimhi, 2015a, 2016). However, to
the best of our knowledge, the status of risk factors as basic negative components of
resilience, and their standing in comparison to protective factors has not been studied
before. This comparison is crucial for determining the significance of risk factors for
the construct of resilience. It is of special importance due to the trend of precluding
risk factors from the definitions of resilience in favor of protective factors which
support coping in face of adversity. The demonstration that risk factors are indeed
valid and independent negative indicators of individual resilience may present a
significant contribution to resilience theory.
Protective factors. Post adversity recovery has been employed as a measure of
protective factors (Kimhi & Eshel, 2009; Kimhi & Shamai, 2004). Israeli research on
the psychological outcomes of war indicated that postwar recovery constitutes a
beneficial psychological resource that helps people to cope with traumatic events, even
though pre-trauma status has not been restored (Kimhi, Eshel, Zysberg, & Hantman,
2010). Post adversity recovery was positively correlated with both individual
resilience and public resilience of elderly people (Kimhi, Hantman, Goroshit, Eshel, &
Zysberg, 2012; Kimhi, Eshel, Leykin Lahad, 2017).
6 Risk factors and resilience
Risk factors. War and terror attacks often give rise to posttraumatic symptoms
which may take the form of delayed emotional and behavioral problems. (Dyregrov,
Gjestad, & Raundalen, 2002), or depression, anxiety, grief, and PTSD (Hadi, Llabre,
& Spitzer, 2006). Distress symptoms represent risk factors in this study.
Individual strength to vulnerability ratio (IND-SVR). IND-SVR is
determined by the ratio of post adversity recovery and level of distress symptoms.
The validity of the IND-SVR index was established by several studies which have
demonstrated the associations of IND-SVR score with various resilience promoting
and resilience suppressing individual attributes (Eshel & Kimhi, 2015, 2016; Eshel et
al., 2016; Eshel, Majdoob & Goroshit, 2014).
Resilience Supporting and Suppressing Factors
Research has shown that personality attributes often play a major role in
adjusting to adversities (e.g., Stroebe & Stroebe, 1987). The present study examines
the associations of five resilience supporting and two resilience suppressing attributes
which have been associated in previous studies with IND-SVR.
Sense of coherence (SOC). SOC is a health-engendering orientation that
functions as a psychologically based stress-resistance resource, which determines
one's ability to cope with harsh events, and to recover from traumatic events
(Antonovsky, 1993). The role of SOC as a resilience supporting factor has widely
been discussed and validated (e.g., Braun-Lewensohn, 2014, 2015; Nilsson, Leppert,
Simonsson & Starrin, 2010).
Well-being. Well-being refers to evaluating quality of life as satisfying and
fulfilling (Diener, Emmons, Larsen, & Griffin, 1985). Well-being was positively
correlated with individual resilience (Eshel & Kimhi, 2015b).
7 Risk factors and resilience
Self-efficacy. Self-efficacy is a dynamic concept that results from the
interplay of cognitive, social, and behavioral skills working together to serve a
specific purpose. It refers to individual’s perceived ability to produce and regulate life
events (Bandura, 1989). The types of activities people engage in, the level of effort
they expend, and their emotional response to these activities are influenced by self-
efficacy.
Social support. Social support is a major stress reducing element, which is an
important resource for coping with adversities and for promoting well-being (Braun-
Lewensohn, 2015; Thoits, 1995). A lack of relationships with significant others has
been linked positively to students' academic stress (Hudson & O'Regan, 1994).
Resources gain. Hobfoll and Lilly (1993) analyzed responses to adversity in
terms of resources gain and resources loss. This theoretical position posits that
resources gain occurs when it results in posttraumatic growth, that is, when different
aspects of life, such as a hope for the future, intimacy with one’s family, or
significance of life, are perceived as improved beyond their pre-traumatic period
level.
Sense of Danger. Wars and acts of terror often breed a sense of danger which
plays an important role in post-terror adaptation (Scott et al. 2012). A continuous
sense of danger may decrease community resilience for a long time after the end of
the adversity which raised it. Solomon et al. (1989) have shown that sense of danger
is negatively correlated with locus of control among Israeli soldiers.
Exposure to distressing experiences. Exposure to war and terror attacks
detrimentally affects resilience (Kimhi & Shamai, 2004). Greater exposure to major
adversities has been correlated positively with level of distress symptoms (Besser,
Zeigler-Hill, Weinberg, Pincus, & Neria, 2015; Scott, Poulin, & Cohen Silver, 2012).
8 Risk factors and resilience
However, it has been found that subjective exposure to terror, that is, fears, worries
and negative thoughts evoked by potentially traumatic events, have major impacts on
adolescents' mental health outcomes (Braun-Lewensohn, Celestin-Westreich, Verte,
Celestin & Ponjaert-Kristoffersen, 2009a, Braun-Lewensohn, Celestin-Westreich,
Verte & Ponjaert-Kristoffersen, 2009b, Solomon & Lavi, 2005).
Previous Israeli studies have established the consistent associations between
resilience supporting and resilience suppressing factors and the IND-SVR index (e.g.
Eshel, & Kimhi, 2015a). The present study aims at establishing the role of risk
factors as major indices of psychological resilience, by validating risk factors (distress
symptoms) as well as protective factors (recovery from extreme adversity)
concurrently against resilience supporting and resilience suppressing attributes. We
assume that these protective factors and risk factors will be consistently and inversely
associated with the investigated attributes. This validation is done by a re-analyses of
published and unpublished data on the responses of the general Israeli public to actual
and potential security threats. These data were gathered after the 2006 war with
Lebanon, after the Mount Carmel fire disaster in 2010, after the 2014 war in the Gaza
Strip, and in a short period of relatively peaceful time. We hypothesize that the
associations of resilience-promoting and resilience suppressing factors with these
protective factors and risk factors will be replicated consistently across the five
studies employed.
The following hypotheses were examined:
1. The impact of resilience promoting and resilience suppressing attributes on a
risk factor component of resilience (i.e., distress symptoms) will be as strong
9 Risk factors and resilience
as its effect on the protective component of this resilience (i.e., recovery from
adversity).
2. The impact of resilience promoting and resilience suppressing factors on a risk
factor component of resilience (i.e., distress symptoms) will be as strong as its
impact on the general resilience score (i.e., IND-SVR).
3. These effects will be replicated in all the five investigated samples, and across
the different adversities involved.
Method
Participants
The 3415 participants in this study constitute 5 samples derived from studies of
individual resilience of Israelis: 1. Adults of the general population who have been
directly affected by the 2006 war with Lebanon (n = 829). 2. Adults who have lived in
greater proximity to, and in remoteness from the 2014 war with Gaza Strip (n = 509).
3. A representative sample of the Jewish population of Israel in relatively peaceful
times in 2015 (n = 1022). 4. Adolescents who were under fire in the 2006 war with
Lebanon (n = 821). 5. Adolescent Druze whose hometown was threatened by the 2010
Mount Carmel fire disaster (n = 234). The two adolescent samples were included in
this study to demonstrate the generality of the role of risk factors in determining
resilience.
Table 1 presenting the demographic characteristics of the participants, shows that
the adult samples represented Israeli Jewish society. They were, on the average, in their
forties, with a range of between 18 and 95 years of age; reported lower than average
income, and para-academic education. They were inclined to hold right-wing political
attitudes, and to be more secular than religious.
Procedure
10 Risk factors and resilience
The research questionnaires were administered to samples 1, 4, and 5 by pen
and paper forms, whereas samples 2 and 3 were recruited by an Israeli online survey
research organization, which employs a panel of over 100,000 subjects, representing
every geographic and demographic sector of Israel. The Ethics Committee of Tel Hai
College approved the research questionnaire. (For the validity of internet
questionnaires see Gosling, Vazire, Srivastava & John, 2004).
Measures
Predicted variables. Three predicted variables were employed in each of the
five studies: recovery from adversity, distress symptoms, and the IND-SVR measure.
Recovery from adversity. Perceived recovery from war experiences was
assessed by a scale devised by Kimhi and associates (Kimhi & Eshel, 2009; Kimhi &
Shamai, 2004). This eight-item scale requested respondents to compare their present
situation with their pre-war situation in eight domains: physical health, morale, social
activity, work, hobbies or sports, emotional state, level of optimism, and hope for a
better future. The response scale ranged from 1 ‘‘much worse than before the war’’ to
5 ‘‘much better than before the war’’. A higher score indicated a higher level of
recovery. The peace time version of this scale pertains to current quality of life
(Eshel, Kimhi, Lahad, & Leykin, 2016). This 9-item version refers to work, health,
recreation, wider social contacts, achievements, family relations, daily functioning,
relations with friends, and general assessment of one's life. The response scale ranged
from 1=not good at all, to 6=very good. The Cronbach reliabilities of this scale in the
investigated samples ranged between α =.82 and α =91.
Distress symptoms. The Brief Symptom Inventory (BSI, Derogatis & Savitz
11 Risk factors and resilience
2000), relating to anxiety, depression, and somatization symptoms was used. This 18-
item inventory is scored on a Likert scale ranging from ‘‘not suffering at all’’ (1), to
‘‘suffering to very much’’ (5). The reliabilities of this scale in the investigated
samples ranged between α = .92 and α = .95.
Individual Resilience. Post-war individual strength to vulnerability ratio (IND-
SVR) was computed for each individual by dividing mean standardized postwar
recovery score by mean standardized level of distress symptoms.
Predicting variables. Five resilience supporting factors (SOC, well-being,
self-efficacy, social support, and resources gains) were investigated in these studies,
as well as two resilience suppressing factors (sense of danger, and exposure to war
adversity).
Sense of coherence (SOC). SOC was measured by a scale devised by
Antonovsky (1993). Responses to this 13-item instrument were rated on a 7-point
scale. Thus, for instance, answers to the item ‘‘Doing the things you do every day is’’,
ranged from (1) ‘‘a source of pain and boredom’’ to (7) ‘‘a source of deep pleasure
and satisfaction’’. Validity and reliability data for this scale are presented in
Antonovsky (1993). The reliabilities of this scale in the investigated samples ranged
between α = .73 and α = .86.
Well-being. Individual well-being was assessed by the Satisfaction in
Life Scale (SWLS) devised by Diener et al. (1985). The response scale for this five-
item instrument ranged between 1 = does not agree at all, to 5 = totally agrees.
The scale’s current reliability was a = .87.
12 Risk factors and resilience
Self-efficacy. The General Self-Efficacy Scale (GSES) examines self-
perceptions of coping with a variety of difficulties in life (Schwarzer & Jerusalem,
1995). Participants rated each of the 10 items (e.g., "If I tried hard enough, I could
always solve difficult problems") on a 5-point Likert scale, ranging from 1 (does not
describe me at all) to 5 (describes me very well). In this study, Cronbach's α was .92.
Social support. Social support was measured by the Multidimensional Scale of
Perceived Social Support (MSPSS; Zimmet et al., 1988). The scale consists of 12
items which are rated on a six-point Likert scale ranging from 1= totally disagree, to
6= totally agree. Cronbach's alpha reliability was .95 in this sample.
Resources gain. The five-item resource gain scale which pertains to perceived
post-adversity improvement (Hobfoll & Lilly, 1993) was employed. A four-point
response scale rated these items ranging from 1 (not improved at all) to 4 (to a great
degree). Its reliability in the two investigated samples was α = .78.
Sense of danger. The sense of safety scale (Solomon and Prager 1992)
pertaining to post-war perceived personal, familial and national danger was employed
(e.g., "To what extent are you afraid that Israel will experience future acts of terror").
This six-item instrument was rated by a Likert-like scale ranging from 1 (not at all) to
5 (very much). These authors found that this scale distinguished Holocaust survivors
who experienced stress from individuals without Holocaust background. The
reliabilities of this scale in the investigated samples ranged between α = .75 and α = .
83.
Exposure to war adversities. Exposure to war was examined by a five-item
scale (four items in two of the samples): "To what extent did you experience adverse
events during the last war?"; "Was your family injured during the war?"; "Were your
13 Risk factors and resilience
friends injured during the war?"; "Did you feel that your life was in danger?"; "Was
your family in danger during the war?" (Eshel et al., 2014; Shamai & Kimhi, 2007).
The 5-point response scale ranged from 1 (not at all), to 5 (very much). The sum of
these ratings determined personal exposure score.
Results
Five path analysis models were conducted by AMOS 19 program for structural
equation modelling (Arbuckle 2009), to determine the contributions of resilience
supporting and resilience suppressing factors to three indices of resilience: IND-SVR,
recovery from adversity, and distress symptoms. These path analyses show (see
Figures 1-5 and Table 2) that as expected well-being, social support, self-efficacy,
resources gain, and SOC, were generally positively associated with IND-SVR and
recovery from adversity, and negatively linked to level of symptoms. Sense of danger
and exposure to terror and war, which are resilience suppressing factors, positively
associated with level of distress symptoms, and negatively correlated with both IND-
SVR and recovery. These replicated results support the contention that protective as
well as risk factors constitute essential parts of individual resilience.
These data show further that the contributions of the predicting variable to the
explained variance of BSI scores were considerably higher than their impact on the
measure of recovery from adversity, in all four studies which followed war or another
disaster. In the fifth study which was conducted in relatively peaceful time, their
contributions to recovery were quite similar to their impacts on distress symptoms.
These findings generally support hypotheses 1. Figures 1-5 and Table 2 also tend to
support hypotheses 2, showing that the impact of the predicting variables on BSI
scores was not lower than their effect on IND-SVR in the four studies which followed
14 Risk factors and resilience
an adversity. Their effect was stronger on the IND-SVR index in the fifth study
which was not associated directly with an extreme hardship. Overall, these data
generally support the replicability of the results across all the five studies.
Discussion
Antonovsky's (1979, 1993) salutogenic model strongly advocates that the study
of resilience should focus on exploring the origin of health rather than on explaining
the causes of disease, and should look for the health-promoting factors within the
individual. This perspective has been adopted by most of the current research on
individual resilience (e.g., Braun-Lewensohn, 2015; Connor & Davidson, 2003;
Egeland, Carlson, & Sroufe, 1993; Luthar et al., 2000). In the past few decades,
resilience theory has shifted away "from looking at risk factors that led to
psychosocial problems to the identification of strengths of an individual’’
(Richardson, 2002, p. 309). Consequently most of the current definitions of
individual resilience practically ignore risk factors.
The underlying assumption supporting this perspective is that posttraumatic
distress symptoms are temporary, and most people show little evidence of more than
transient disruptions in functioning after a major adversity (Bonanno & Mancini,
2012). The general public indeed eventually returns to a normal pre-adversity level of
functioning. However, this normal performance does not indicate a disappearance of
distress symptoms. It is more likely that normal performance reflects a level of
recovery strategies which is stronger than the risk factors, so that positive adaptation
is achieved despite the presence of lingering symptoms. A factor analysis of the
responses of Israeli Muslim widows has thus found that they keep suffering despite a
high level of resilience which helps them carry on their familial and social duties
(Yasien-Esmael, Eshel & Rubin, 2017).
15 Risk factors and resilience
The present replication study seems to question the empirical basis of
definitions of resilience which are based solely on individual recovery from adversity
(Bonanno, 2005; Braun-Lewensohn, 2015), and raise the question of whether the
rejection of risk factors from these definitions could have been somewhat premature.
The repeated findings on the major role of risk factors in determining resilience in
face of adversity, which were demonstrated by the present data, strongly suggest that
risk factors should be reintegrated into definitions of resilience. The IND-SVR index
has been found as a valid measure of resilience in a number of recent studies (e.g.,
Eshel, 2016; Eshel & Kimhi, 2015a, 2016; Eshel et al., 2014). The present data show
further that the variance of distress symptoms explained by resilience supporting and
resilience suppressing factors is not lower than the explained variance of the IND-
SVR index. These findings show that under stressful conditions level of distress
symptoms constitutes (a negative) indicator of resilience whose impact on
readjustment may be as high as the effect of IND-SVR. These results were practically
replicated in the four studies which were conducted under extreme security threats.
It has been argued that the coping with adversity process depends on resources
variables (Braun-Lewensohn, 2015). The present findings support the contention that
strengthening protective factors, as well as overcoming risk factors, are essential parts
of the struggle between salutogenic and pathogenic components which characterizes
the process of reestablishing post-adversity positive adaptation (Masten, 2011).
Protective factors and risk factors are required for defining psychological resilience as
an ongoing process of readjustment to changing and stressful conditions.
Israeli studies have found that the psychological health of individuals exposed
to recurring terror attacks, is negatively affected by the anxieties and worries aroused
by terror threats than by the extent of exposure to them (Braun-Lewensohn et al.,
16 Risk factors and resilience
2009a; Solomon & Lavi, 2005). The present data replicate these findings: the impact
of exposure to terror attacks on indices of resilience is generally lower than the effect
of the sense of danger which is associated with them.
Resilience is a dynamic state of mind that may change due to changing
circumstances (Ungar, 2011) which will modify the existing balance of individual
protective factors and risk factors. The clinical implication of the present data seems
to be that a therapist who wishes to improve patients' resilience may achieve this goal
by enhancing protective forces, as well as by decreasing anxiety and depression.
Limitations of this study. Four limitations of this study should be referred to.
First, all the studies employed were conducted in Israel which is plagued by wars and
acts of terror. Demographic and cultural factors, as well as prior traumatic experience
may change the effects of resilience supporting and resilience suppressing variables
(Braun-Lewensohn et al., 2009b). The role of risk factors in establishing resilience
should be investigated further in other settings which are more peaceful than the
Israeli setting to determine their generality. Second, individual resilience was
assessed in these studies by the proportion of protective and risk factors. Future
research should examine the role of risk factors in the process of resilience by means
of additional measures of resilience. Third, all the present data are cross-sectional and
retrospective. Longitudinal and prospective studied are required to further support
our conclusions. Fourth, the present study has employed self-report measures of
resilience. Future research should find additional, behavioral methods of assessing
resilience (e.g., Braun-Lewensohn, 2009a).
Despite these shortcomings the present study has a main merit. The present
findings present convincing evidence showing that risk factors are legitimate, valid,
and useful parts of the definition of psychological resilience. It was indicated above
17 Risk factors and resilience
that the focus of resilience research has shifted away in the last decades to
investigating the process through which individuals overcome the hardships they
encounter (Luthar et al., 2000). Other theorizing (Kimhi & Eshel, 2015) as well as
the present data may suggest that this shift should be reexamined.
Conflict of interest: none
Human and Animal Rights and Informed Consent. This article does not contain
any studies with human or animal subjects performed by any of the authors.
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Table 1: Demographic characteristics of the investigated samples
Participants' characteristics
Sample Mean
Age
Years of
education
Family
Income*
Political
attitude●
Religiosity♦ Percentage
of females
Adults, 2006
Lebanon war
(N=870)
M
s.d
.
44.12
16.15
12.94
2.92
2.53
1.30
2.52
.91
1.71
.76 59.7
High school
students, 2006
Lebanon war,
(N=821)
M
s.d
.
15.04
1.54
9.09
1.44
3.00
1.21 --
1.58
.64 51.9
High school
students, 2010
Fire disaster
(N=234)
M
s.d
.
16.73
.84
8.28
.73
3.17
1.25 -- -- 6.29
Adults, 2014
Gaza war
(N=510)
M
s.d
.
42.15
15.52
Para-
academic
2.66
1.17
2.59
.92
1.64
.93 50.4
Adults, 2015
(N=1022)
M
s.d
.
43.56
16.09
Para-
academic
2.51
1.09
2.42
.88
1.83
.92 48.2
*Family income: 1=much less than average, 2=less than average, 3=average, 4=above
average, 5=much above average
●Political attitude: 1=extreme right, 2=right, 3=center, 4=left, 5=extreme left
♦Religiosity: 1=secular, 2=traditional, 3=religious, 4=orthodox
24 Risk factors and resilience
Table 2: Paths Predicting Three Indices of Resilience in Each of Five Independent
Studies, Standardized Regression Coefficients and Percentage of Explained
Variance
R 2
Resilience indexBetaPathStudy
.44IND_SVR .46***SOC to IND_SVRAdults 2006
(N=870) .19Recovery .28***SOC to Recovery
.46Stress symptoms-.42***SOC to Symptoms
.07*Resources gain to IND_SVR
.13*Resources gain to Recovery
-.06*Resources gain to Symptoms
-.33***Sense of danger to IND_SVR
-.21***Sense of danger to Recovery
.38***Sense of danger to Symptoms
-.06*Exposure to IND_SVR
-.04Exposure to Recovery
-.05*Exposure to Symptoms
.28IND_SVR .24***Resources gain to IND_SVRHigh school
students 2006
(N=821)
.21Recovery .43***Resources gain to Recovery
.31Stress symptoms-.10**Resources gain to Symptoms
-.47***Sense of danger to IND_SVR
-.19***Sense of danger to Recovery
.54***Sense of danger to Symptoms
-.10**Exposure to IND_SVR
-.04Exposure to Recovery
.09**Exposure to Symptoms
.19IND_SVR .39***SOC to IND_SVRMount
Carmel Fire,
High school
students 2010
(N=234)
.01Recovery .07SOC to Recovery
.34Stress symptoms-.49***SOC to Symptoms
-.16**Exposure to IND_SVR
-.07Exposure to Recovery
.27***Exposure to Symptoms
.39IND_SVR .28***Well-being to IND_SVRAdults 2014
(N=510) .12Recovery .19***Well-being to Recovery
.46Stress symptoms-.30***Well-being to Symptoms
.26***SOC to IND_SVR
-.01SOC to Recovery
-.36***SOC to Symptoms
-.23***Sense of danger to IND_SVR
-.21***Sense of danger to Recovery
.18***Sense of danger to Symptoms
-.14***Exposure to IND_SVR
-.07Exposure to Recovery
.15***Exposure to Symptoms
.56IND_SVR
.42***
SOC to IND_SVRAdults, 2015
.49Adjustment .29***SOC to Adjustment
25 Risk factors and resilience
(N=1022) .44Stress symptoms-.44***SOC to Symptoms
.12***Self-efficacy to IND_SVR
.14***Self-efficacy to Adjustment
-.06*Self-efficacy to Symptoms
.32***Social support to IND_SVR
.43***Social support to Adjustment
-.11***Social support to Symptoms
-.10***Sense of danger to IND_SVR
-.03Sense of danger to Adjustment
.18***Sense of danger to Symptoms
-.11***Exposure to IND_SVR
-.07**Exposure to Adjustment
.16***Exposure to Symptoms
*p< .05, **p< .01, ***p< .001
Figure 1: Path Analysis Predicting IND-SVR, Recovery, and BSI Scores of Adults
Following the 2006 Second Lebanon War (N=870)
26 Risk factors and resilience
Figure 2: Path Analysis Predicting IND-SVR, Recovery, and BSI Scores of High
School Students Following the 2006 2nd Lebanon War (N=821)
Figure 3: Path Analysis Predicting IND-SVR, Recovery, and BSI Scores of Druze
Adolescents Following the Mount Carme Fire Disaster 2011 (N=234)
27 Risk factors and resilience
Figure 4: Path Analysis Predicting IND-SVR, Recovery, and BSI Scores of Adults
Following the 2014 Gaza War (N=510)
Figure 5: Path Analysis Predicting IND-SVR, Current Adjustment, and BSI
Scores of a Representative Sample of Israeli Adult Jews 2015 (N=1022)
28 Risk factors and resilience
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