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Journal of Loss and Trauma
International Perspectives on Stress & Coping
ISSN: 1532-5024 (Print) 1532-5032 (Online) Journal homepage: http://www.tandfonline.com/loi/upil20
Individual, Community, and National Resilience
in Peace Time and in the Face of Terror: A
Longitudinal Study
Shaul Kimhi, Yohanan Eshel, Dmitry Leykin & Mooli Lahad
To cite this article: Shaul Kimhi, Yohanan Eshel, Dmitry Leykin & Mooli Lahad (2017) Individual,
Community, and National Resilience in Peace Time and in the Face of Terror: A Longitudinal Study,
Journal of Loss and Trauma, 22:8, 698-713, DOI: 10.1080/15325024.2017.1391943
To link to this article: https://doi.org/10.1080/15325024.2017.1391943
Accepted author version posted online: 27
Oct 2017.
Published online: 28 Nov 2017.
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JOURNAL OF LOSS AND TRAUMA
2017, VOL. 22, NO. 8, 698–713
https://doi.org/10.1080/15325024.2017.1391943
Individual, Community, and National Resilience in Peace
Time and in the Face of Terror: A Longitudinal Study
Shaul Kimhia, Yohanan Eshela, Dmitry Leykinb, and Mooli Lahadc
aPsychology Department, Tel Hai College, Tel Hai, Israel; bRecanati School for Community Health
Professions, Ben-Gurion University of the Negev, Beer-Sheva, Department of Emergency Medicine,
Faculty of Health Sciences, Israel; cTel Hai College, Community Stress Prevention Center, Kiryat
Shemona, Israel
ABSTRACT
The present paper is based on thrice-repeated measures. The
sample constituted 561 Jewish Israeli adults who experienced
these terror attacks. The study examined individual, community
and national resilience and their associations with resilience-
promoting factors (sense of coherence, social support, and
self-efficacy); as well as resilience-suppressing factors (distress
symptoms, sense of danger, and exposure). Results indicated
that resilience scores were quite stable across the three
repeated measures, whereas sense of coherence, distress
symptoms, sense of danger, and exposure significantly changed
across the three repeated measures. Sense of coherence was
the best predictor for individual, community, and national
resilience.
ARTICLE HISTORY
Received 9 October 2017
Accepted 10 October 2017
KEYWORDS
Community resilience;
individual resilience;
longitudinal research;
national resilience; stability
and change of resilience;
terrorism
The present longitudinal study employs pre-adversity measures as predictors
of postdiversity resilience. The following issues are examined: To what extent
do resilience-promoting and suppressing factors change following terror
attacks? To what degree do sense of coherence, social support, self-efficacy,
and level of exposure, in peaceful times, predict individual, community, and
national resilience under future terror attacks? Do individual, community,
and national resilience remain stable across three repeated measurements
during a wave of terror?
A literature review indicates that there are many definitions of resilience
(Bonanno, Romero, & Klein, 2015). Earlier definitions of resilience empha-
sized deficit-based pathogenic processes such as levels of distress symptoms
after a major adversity. In the last decades, resilience theory has shifted away
“from looking at risk factors that led to psychosocial problems to the identi-
fication of strengths of an individual” (Richardson, 2002, p. 309). Resilience
has thus been defined as “protective factors which modify, ameliorate or
alter a person’s response to some environmental hazard that predisposes
to a maladaptive outcome” (Rutter, 1987, p. 316; 2006). Similarly, other
none defined
CONTACT Prof. Shaul Kimhi shaulkim@telhai.ac.il; shaul@shamir.org.il Psychology Department, Tel Hai
College, 12210, Israel.
© 2017 Taylor & Francis Group, LLC
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researchers have defined resilience as people’s ability to withstand stress and
adversity (Bonanno, 2004; Suedfeld, 2015).
Our theoretical position is that resilience should be determined concur-
rently by strength and vulnerability and should reflect the balance between
protective factors and risk factors (e.g., Masten, 2011). We define resilience
as the ratio of perceived strength (protective factors) to vulnerability (risk
factors; SVR), following an adversity or a potentially traumatic event, at the
individual, community, or national levels. This definition of resilience is
supported by recent Israeli studies (Eshel & Kimhi, 2016a).
In the current study, we examined resilience change and stability using SVR
indices, which are based on resilience scale scores divided by vulnerability
scale scores. In addition, we examined resilience-promoting and suppressing
factors as predictors of resilience across the three measures. There are
earlier prospective resilience studies (Hjemdal, Friborg, Stiles, Rosenvinge,
& Martinussen, 2006). However, this is one of the few studies that has
managed to collect data from the same participants both prior and after a
potentially traumatic event.
Change and stability of resilience
Resilience is described as a dynamic adjustment process that changes
according to contextual modifications (Fletcher & Sarkar, 2013). Thus, for
instance, exposure to the September 11, 2001, terror attacks resulted in higher
levels of patriotism among Americans (Moskalenko, McCauley, & Rozin,
2006). Sense of resilience and distress symptoms are bound to change accord-
ing to individual interpretation of the situation. However (Bonanno, 2004;
Bonanno, Romero, & Klein, 2015) has posited that the vast majority of people
retrieve a sufficient degree of resilience following adversity, despite a degree of
distress symptoms.
Individual resilience
A literature review has indicated that most of the research on resilience
pertains to individual resilience. It appears that individual resilience is a key
issue in buffering negative psychological consequences of major adversities
(Kimhi & Eshel, 2009; Suedfeld, 2015). According to our definition in this
study, individual resilience is the individual strength and vulnerability ratio
(IND-SVR).
Community resilience
Cacioppo, Reis, & Zautra (2011) defined social resilience as “the capacity to
foster, engage in, and sustain positive relationships and to endure and recover
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from life stressors and social isolation” (p. 44). Community resilience
expresses the interaction between individuals and their community and per-
tains to the ability of individuals to get help from their community, and the
ability of the community to help individuals and provide for their needs.
According to our reasoning, community strength-to-vulnerability ratio
(COM-SVR) will be determined by community resilience scale scores divided
by sense of danger (Leykin, Lahad, Cohen, Goldberg, & Aharonson-Daniel,
2013).
National resilience
Several studies have referred to resilience as a wider societal phenomenon,
and have investigated it in terms of national resilience (Chemtob, 2005) or
social resilience (Cacioppo, Reis, & Zautra, 2011). Four main social compo-
nents have been attributed to national resilience (Ben-Dor et al., 2002):
patriotism, optimism, social integration, and trust in political and public insti-
tutions. One of a few studies of antecedents of NAT-SVR (national resilience
scale scores divided by sense of danger) has shown that NAT-SVR was
positively predicted by sense of coherence, well-being, and economic
condition (Eshel & Kimhi, 2016b).
Resilience-promoting and suppressing factors
Sense of coherence
The sense of coherence (SOC) concept comprises three interrelated compo-
nents: sense of meaningfulness, comprehensibility, and manageability. Hence,
SOC affects how individuals perceive the world and the events that happen to
them as well as the extent to which they perceive these events as controllable.
SOC is a major element of Antonovsky’s theory (1993; 1987). According to
this theory, higher SOC indicates an ability to cope with adversities such as
war (Braun-Lewensohn & Sagy, 2014). Earlier studies indicated that higher
SOC has been associated positively with greater resilience (Ebert, Tucker, &
Roth, 2002).
Social support
Social support from significant others, family, and friends is a major
stress-reducing element among university students. Social support is inversely
correlated with students’ stressful life events, and negative emotional reactions
(El-Ghoroury, Galper, Sawaqdeh, & Bufka, 2012), and lack of a relationship
with a significant other was positively associated with students’ academic
stress (Hudson & O’Regan, 1994).
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Self-efficacy
The construct of perceived self-efficacy reflects an optimistic self-belief, and
refers to people’s beliefs about their capacity to exercise control over events
that affect their lives in order to manage prospective situations. Perceived
self-efficacy influences the goals people set, the effort they invest in attaining
those goals, and their resilience when faced with difficulties (Bandura, 1997).
Research shows that the self-efficacy score has been positively correlated with
individual levels of engagement toward a specific goal, and with levels of per-
severance (Silvia, 2006). We hypothesize that the three resilience-promoting
factors will be positively associated with all three SVR measures of resilience.
Distress symptoms
War and terror attacks are highly painful events, which shake people’s basic
sense of security and give rise to posttraumatic symptoms. These symptoms
include delayed emotional and behavioral problems (Soffer-Dudek, 2016)
such as depression, anxiety, and grief (Hadi, Llabre, & Spitzer, 2006).
Sense of danger
Lazarus & Folkman (1984) claim that perceived postadversity distress and
assessment of stress-resistant resources reflect cognitive appraisals. A linger-
ing sense of danger, which may decrease individual resilience, plays a major
role in postwar adaptation (e.g., Scott, Poulin, & Cohen Silver, 2012).
Level of exposure
Exposure to terror attacks detrimentally affects resilience (Kimhi & Shamai,
2004). A higher level of exposure has been associated with a higher level of
distress symptoms (Besser et al., 2015). However, exposure to adversities
has not predicted dysfunction in some Israeli studies (Bleich, Gelkopf, &
Solomon, 2003). We hypothesize that exposure will be negatively associated
with all three SVR measures of resilience (keep in mind that sense of danger
and distress symptoms are part of the calculation of SVR and are not part of
the hypothesis).
Background
This longitudinal design research is based on three repeated measures pertain-
ing to a recent wave of terror attacks, which took place in Israel. The first
measurement was conducted in a relatively peaceful period before the terror
wave, as a baseline for possible future traumatic events (July 2015, with three
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nonfatal casualties, and no deaths due to terror attacks). The second measure-
ment took place at the height of the wave, one month after the beginning of
the attacks (October 2015, during which the terror toll was 11 deaths and 80
nonfatal casualties); the third measurement was administered six months
later, toward a decline in the terror attacks (April 2016, 18 nonfatal terror
casualties). This wave of terror was mainly characterized by almost daily
stabbing attacks carried out by Palestinian individuals against Israeli Jews
(Information Center for Intelligence and Terrorism, 2015). Against this
background, the main purpose of this study was to examine individual, com-
munity, and national resilience of Israelis facing the threat of daily terror
attack, and to measure stability and change in their resilience and its
components.
During the present wave of terror, most of our participants were exposed to
terror attacks via the media and not directly (Information Center for Intelli-
gence and Terrorism, 2015). In addition, the Israeli public has been living
with the intractable Arab-Israeli conflict for a long time, and is well aware that
future terror attacks may happen anytime and anywhere (Bleich et al., 2003).
We assumed accordingly that living with terror has helped the Israeli public to
develop a positive balance of strength and distress, which is not substantially
shaken by further acts of terror and resilience, and would remain stable across
the wave of terror. However due to scarcity of available research, this issue will
be examined as an open research question.
Hypotheses
1. Resilience-promoting factors will be lower at the second measurement,
compared with the baseline level, and will return to baseline level at the
third measurement, while resilience-suppressing factors will be higher at
the second measurement, compared with both the first and the third
measurements, and will return to baseline level at the third measurement.
2. Resilience-promoting factors will significantly and positively predict SVR
resiliencies, while level of exposure will significantly and negatively predict
SVR resiliencies, across the three repeated measurements.
3. We will examine as an open question whether or not individual,
community, and national SVR resilience scores will remain stable across
the three repeated measurements.
Method
Data collection and sampling
This longitudinal research compares civilian resilience in a relatively peaceful
time (June 2015) with resilience in a period of more intensive terror attacks
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(October 2015), and in a period of less intensive terror acts (April 2016). The
first measure included 1,022 Jewish Israeli adults, and the repeated second
measure was obtained from 740 (72%) of them who responded for the second
time. The third repeated measure included 561 participants (76% of the
second measure) who responded to the questionnaire for the third time,
and provided all the requested data (see participants’ details in Table 1).
The current research data are based on participants who responded to all
three measurements. Table 1 describes the demographic characteristics of
our participants.
Recruiting of participants was conducted by an Israeli online survey
research organization, which employs a panel of over 100,000 subjects, repre-
senting every geographic and demographic sector of Israel (http://www.ipanel.
co.il/; for the validity of Internet questionnaires, see Gosling, Vazire,
Srivastava, & John, 2004). Data collection was carried out using an online
panel. The panelists were prerecruited to respond to surveys and were there-
fore willing and able to participate. The Internet organization uses the strati-
fied sampling method, based on data published by the Israeli Central Bureau
of Statistics, and determines quotas by age and gender. Each participant
signed an informed consent form. Tel Hai College Ethics committee approved
the questionnaire. A comparison of the demographic characteristics of the 561
Table 1. Distribution of demographic characteristics of investigated sample (N ¼561).
Variable Scale/range n %
Age 18–45 315 56.1
46–65 170 30.3
66–91 76 13.5
Education
1
1–2 ¼elementary, high 55 10.0
3–4 ¼nonacademic 204 37.0
5–6 ¼university 292 53.0
Gender 1 ¼female 278 49.6
2 ¼male 283 50.4
Average family Income 1 ¼much less 115 20.5
2 ¼less 171 30.5
3 ¼average 163 29.1
4 ¼above 89 15.9
5 ¼much above 23 4.1
Political preference 1 ¼much right 60 10.7
2 ¼right 226 40.3
3 ¼center 202 36.0
4 ¼left 67 11.9
5 ¼much left 6 1.1
Religiosity 1 ¼secular 250 44.6
2 ¼traditional 198 35.3
3 ¼religious 54 11.4
4 ¼orthodox 49 8.7
Exposure to terror time 2 5–10 ¼low 486 86.6
11–15 ¼medium low 59 10.5
16–20 ¼medium high 13 2.3
21–25 ¼high 3 0.5
Note:
1
10 participants indicated “other” as their education level.
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respondents with the 282 participants, who did not respond to the second and
third administration of the questionnaire, indicated no significant differences
between the two groups.
Tools
Individual resilience
The present measure of individual resilience, “My Life Today,” is based on the
Recovery from War Scale (Kimhi & Eshel, 2009; Kimhi & Shamai, 2004). This
9-item self-report scale describes present individual strengths in the domains
of work, health, recreation, wider social contacts, achievements, family rela-
tions, daily functioning, relations with friends, and general assessment of
one’s life. The 6-point response scale ranges from 1 ¼not good at all to
6 ¼very good. The scale’s reliability for all three measurements was a ¼.91.
Distress symptoms
The Brief Symptom Inventory (BSI, Derogatis & Savitz, 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 very much” (5). The scale’s reliability in the three measurements
was a ¼.92.
Postwar recovery-to- distress symptoms ratio
IND-SVR resilience score was determined by dividing mean standardized
“My Life Today” score by mean standardized level of distress symptoms
(BSI) score.
Community resilience
A short version of the Conjoint Community Resiliency Assessment Measure
(Leykin, Lahad, Cohen, Goldberg, & Aharonson-Daniel, 2013) was employed.
This version included 10 items pertaining to identification with one’s
community (“I am proud to tell people where I live”), trust in municipal
authorities, and confidence in the community’s ability to withstand adversi-
ties. The 5-point response scale ranged from 1 ¼does not agree at all,
to 5 ¼totally agrees. The scale’s reliabilities in the three measurements were
a ¼.91 and a ¼.92.
Sense of danger
The Sense of Danger Scale (Solomon & Prager, 1992) pertaining to postwar
perceived personal, familial, and national danger was employed (e.g., “To
what extent are you afraid that Israel will encounter future acts of terror?”).
This six-item instrument was rated on a Likert-like scale ranging from
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1 (not at all) to 5 (very much). The scale’s reliabilities ranged between a ¼.85
and a ¼.92.
Community strength to vulnerability ratio (COM-SVR)
COM-SVR resilience was determined by the standardized community resili-
ence score divided by the standardized sense of danger score.
National resilience assessment scale (NRAS)
The NRAS scale is based on Kimhi, Goroshit, and Eshel (2013). The scale
includes 25 items and refers to trust in leadership, trust in the Israeli Defense
Forces, patriotism, optimism, and trust in major national institutions. The
6-point response scale ranged from 1 ¼(very strongly disagree) to 6 ¼(very
strongly agree); for example, “I love Israel and feel proud to be an Israeli.”
The scale’s reliability in each of the three measurements was a ¼.92.
National strength-to-vulnerability ratio (NAT-SVR)
Standardized NRAS scores divided by standardized sense of danger scores
determined this scale.
Sense of coherence (SOC)
A scale devised by Antonovsky (1993) measured SOC. Responses to this
13-item instrument were rated on a 7-point scale. For example, 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 scale’s reliabilities in the three measurements were a ¼.83, .85
and .86 respectively.
Social support
Social support was measured using the Multidimensional Scale of Perceived
Social Support (Zimmet, Dahlin, Zimmet, & Farley, 1988). The scale consists
of 12 items rated on a 7-point Likert scale (1 ¼totally disagree and 7 ¼totally
agree). Cronbach’s alpha was .95 in the three present measurements.
Self-efficacy
The General Self-Efficacy Scale (Jerusalem & Schwarzer, 1992) was employed.
This 10-item self-rating scale assesses perceived successful coping (e.g., “I can
always manage to solve difficult problems if I try hard enough”), and is posi-
tively correlated with level of perseverance (Silvia, 2006). A four-point
response scale was employed with 1 ¼not at all true, and 4 ¼completely true.
In samples from 23 nations, Cronbach’s alphas ranged from 0.76 to 0.90. The
scale’s reliability in the three measurements was a ¼.92.
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Level of exposure
Level of exposure to terror adversities was examined by a questionnaire based
on an instrument devised by Heath, Hall, Russ, Canetti, & Hobfoll (2012),
which pertains to being negatively impacted by acts of terror or war in the last
year. The sum of these five items determined exposure score. Previous
research has found that higher exposure to adversity is associated with higher
stress (Shamai, & Kimhi, 2007).
Results
As a first step, we calculated Pearson correlations among the research
variables (Table 2). Results indicated that the three resilience indices corre-
lated significantly (p < .05) and positively with resilience-promoting factors
and significantly and negatively with resilience-suppressing factors, across
the three measurements.
Our first hypothesis was examined by GLM (General Linear Model
Repeated Measures, provides both univariate and multivariate analyses)
conducted for the three resilience SVR scores, resilience-promoting and
suppressing factors (Table 3). Results indicated the following: (a) SOC signifi-
cantly decreased from measurement one to two (p < .000) and increased from
measurement two to three (p ¼.03). Both linear and quadratic main effects
were significant (Partial Eta squares ¼.013 and .000 respectively). (b) Social
support as well as self-efficacy did not change significantly across the three
measurements. These results only partially support our second hypothesis
Table 2. Pearson correlations among individual, community and national resilience, promoting
and suppressing factors across three measurements (N ¼561).
Variables Time of measurement IND-SVR COM-SVR NAT-SVR
SOC t1 Base line .565*** .277*** .293***
t2 October 15 .553*** .334*** .348***
t3 April 16 .631*** .363*** .349***
Social support t2 .555*** .252*** .162***
t2 .557*** .183*** .089*
t3 .619*** .259*** .122**
Self-efficacy t2 .391*** .148*** .160***
t2 .422*** .173*** .126***
t3 .397*** .188*** .130***
Distress symptoms t2 –
1
–.316*** –.333***
t2 – –.416*** –.428***
t3 – –.365*** –.343***
Sense of danger t2 –.303*** –
1
–
1
t2 –.344*** – –
t3 –.273*** – –
Level of exposure t2 –.232*** –.167*** –.186***
t2 –.337*** –.261*** –.312***
t3 –.201*** –.225*** –.242***
Note. *p < .05, **p < .01, ***p < .001.
1
Cells are empty due to the fact that variables appear in the calculation
of SVR.
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regarding resilience-promoting factors. (c) All three suppressing factors
significantly (p < .001) changed across the three measurements: Distress
symptoms were significantly higher at the second measurement, compared
with baseline level and significantly lower at the third measurement,
compared with both the first and second measurement. Sense of danger
was significantly higher at the second measurement, compared with baseline
level, and similar to baseline at the third measurement. Exposure to terror
experience was significantly higher at the third measurement compared with
the first and the second measurements. These results mainly supported our
first hypothesis regarding resilience-suppressing factors.
To examine our second hypothesis and to clarify the relative importance of
promoting factors and level of exposure, we launched a path analysis
(Arbuckle, 2009): SOC, social support, self-efficacy, and exposure at T1
predicting individual, community and national resilience SVR in each of
the three measurements (saturated models, which examine all paths and
correlations, see Table 4 and Figure 1). We did not examine distress
symptoms and sense of danger since they served as denominators for the
calculation of SVR.
Results indicated the following: (a) SOC significantly and positively pre-
dicted individual, community, and national resilience SVR (p < .001) across
the three repeated measurements. SOC is the best predictor of individual,
community, and national resilience at each of the three measurements (except
that social support predicted individual and community resilience at baseline
level). (b) Social support significantly and positively predicted individual and
community resilience across the three repeated measurements (except for
Table 3. General linear model—thrice-repeated measure: SVR resilience, resilience-promoting,
and suppressing factors (N ¼561).
Variable/Measurement First Second Third F ή
2
IND-SVR M 1.079 1.075 1.073 .110 .000
SD .397 .393 .390
COM-SVR M 1.068 1.074 1.074 .129 .000
SD .390 .408 .406
NAT-SVR M 1.075 1.081 1.087 .387 .001
SD .406 .429 .441
SOC M 5.058
a
4.845
b
5.133
c
71.008*** .113
SD .981 .872 .982
Social support M 4.926 4.905 4.918 .232 .000
SD .994 1.069 1.028
Self-efficacy M 3.253 3.255 3.276 1.406 .002
SD .548 .560 .560
Distress symptoms M 1.511
s
1.577
b
1.460
c
21.342*** .037
SD .509 .539 .503
Sense of danger M 2.298
a
2.525
b
2.322
ca
43.971*** .074
SD .732 .770 .717
Exposure to terror M 6.916
a
7.090
a
7.963
b
44.441*** .074
SD 2.664 2.658 2.856
Note. ***p < .001.
a, b, c
Adjustment for multiple comparisons: Bonferroni.
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community resilience in October), but was almost unrelated to national
resilience. (c) Self-efficacy significantly and positively predicted individual
resilience in July and October (p < .001). Self-efficacy did not predict
community or national resilience at all three measurements. (d) As expected,
the resilience-promoting psychological factors explained a much higher
percentage of individual resilience variance (about 50%) compared with
community (9% to 16%) and national resilience (8% to 16%). (e) Interestingly,
the examined four variables predicted higher levels of resilience during the
height of the terror attacks (second measurement).
To examine our research question, we calculated Pearson correlations among
the three SVR scores across the three measurements. No significant changes
were found for IND-SVR, COM-SVR, or NAT-SVR across the three repeated
measures. In other words, our results indicated that individual, community,
and national resilience remain stable cross the three repeated measurements.
Table 4. General model of promoting factors and exposure as predictors of resilience SVR
indices: Beta values for thrice-repeated measurements and percent of explained variance.
Paths Overall % of explained variance (R2)
Predictor t1
Predicted model
path1 t1 July t2 October t3 April t1 t2 t3
SOC 1-IND-SVR .231*** .539*** .485*** IND-SVR .507 .581 .485
2-COM-SVR .124** .357*** .240*** COM-SVR .095 .168 .109
3-NAT-SVR .190*** .387*** .274* NAT-SVR .078 .161 .091
Social support 4-IND-SVR .514*** .327** .278***
5-COM-SVR .240*** .096 .107*
6-NAT-SVR .097* –.006 –.012
Self-efficacy 7- IND-SVR .139*** .053 .071
8-COM-SVR .012 –.025 .023
9-NAT-SVR .069 –.031 –.007
Exposure 10-IND-SVR –.064* –.093 –.119***
11-COM-SVR .034 -.083 -.092*
12-NAT-SVR –.004 –.094 –.103*
Note. *p < .05, **p < .01, ***p < .001.
1
Numbers represent the path in Figure 1.
Figure 1. General model of promoting factors and exposure as predictors of individual,
community, and national resilience SVR indices.
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Discussion
We examine three main issues in our study: First, we examined resilience-
promoting and suppressing factors as predictors and correlates of the three
modes of resilience. Second, we examined the prediction of sense of
coherence, social support, self-efficacy, and level of exposure (controlling
for each other) for the three modes of resilience across the three repeated
measurements. Third, we examined stability versus changes of individual,
community, and national resilience under three different intensity levels of
terror attacks.
Our data regarding promoting and suppressing factors supported previous
studies that validated the IND-SVR, COM-SVR, and NAT-SVR measures by
demonstrating their positive correlations with resilience-promoting factors,
and their negative associations with resilience-suppressing factors (Eshel &
Kimhi, 2016; Eshel & Majdoob, 2014). The present data show that all three
SVR scores were significantly and negatively correlated with the three
suppressing factors (distress symptom, sense of danger, and exposure) and
significantly and positively with the three promoting factors (SOC, social
support, and self-efficacy).
Our results corroborate earlier studies indicating that SOC significantly
predicts measures of resilience (Braun-Lewensohn & Sagy, 2014; Ebert,
Tucker, & Roth, 2002; Eshel & Kimhi, 2015). SOC is a general perspective
on life, which functions as a psychologically based stress-resistance resource,
constituting a major determinant of one’s ability to cope with harsh events
such as war (Antonovsky, 1987). Accordingly, SOC positively correlated with
IND-SVR, COM-SVR, NAT-SVR, and individual, community, and national
resilience scale scores, and negatively correlated with exposure to terror acts.
In addition, our results regarding social support corroborate other studies that
emphasize the importance of social support in coping with stress situations
(El-Ghoroury, Galper, Sawaqdeh, & Bufka, 2012). It may be assumed that
stability of social support contributes to the stability of individual resilience.
Results also indicated that the three resilience-promoting variables (SOC,
social support, and self-efficacy) better explained variance of individual
resilience SVR, compared with community and national resilience SVR. This
finding may be explained by the fact that individual resilience is a personal
characteristic, whereas community and national resiliencies refer to people’s
feelings about the management of larger groups. It appears that other charac-
teristics, such as community type, level of religiosity, and age, will constitute
better predictors of public resiliency (e.g., Kimhi, Goroshit & Eshel, 2013).
In addition, our study indicated an impressive stability of SVR resilience,
which did not change much across the three measurements: before the wave
of terror occurred, at the height of this terror wave, and its decline (Bleich,
Gelkopf, & Solomon, 2003). This stability was maintained in spite of the
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finding that SOC (but not social support and self-efficacy), distress symptoms,
sense of danger, and level of exposure had changed significantly throughout
this wave of terror attacks. Bonanno, Romero, and Klein, 2015 have claimed
that the majority of people are resilient since they generally exhibit a stable
trajectory of healthy functioning across time, and return to a normal level
of daily activities a short time after a potentially traumatic event. The present
data show that, in accord with our theoretical analysis, adult Israeli Jews have
developed a high level of habituation to living with this terror. The present
data do not show that most of the participants have become resilient following
potentially traumatic events. They do show that regardless of being more
or less resilient, they have managed to maintain their characteristic level of
resilience despite pronounced threats of terror.
An additional explanation for the stability of resilience is the fact that terror
attacks directly affected only a very small number of people, and most of our
participants were exposed to this wave of terror via the media. The data indicate
that the mean scores of exposure in the three measurements did not exceed the
eight levels on a scale ranging from 5 to 25. We assume that a higher level of
threat (such as war or a major national disaster) would result in higher stability
of the SVR ratios. Further longitudinal studies following national adversity
should be conducted in order to support this assumption.
Limitations
Among the limitations of this study, we may mention the following: First, this
longitudinal study is based on a rather short interval between the measure-
ments (about 10 months). A longer interval might have yielded different
results. Second, by definition, waves of terror have direct effects on a relatively
small number of people. It is quite possible that a full-scale war would have
resulted in a greater impact on resilience SVR scores. Third, the present data
are based on a sample that was reached by Internet. This fact may have biased
the representativeness of our sample.
Conclusions
Despite these limitations, we believe that this study has three major strengths.
First, the data present perhaps the first longitudinal evidence that people tend
to retain their characteristic level of individual, community, and national resili-
ence, despite dramatic changes in the level of terror which they experience.
Second, our data supported the role of resilience-promoting and suppressing
factors across three repeated measures. Third, the study substantiates the role
of SVR resilience indices as effective measures of individual, community, and
national resilience. These findings call for a new perspective on the nature of
resilience, and how it should be determined in future research.
710 S. KIMHI ET AL.
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Funding
This study was supported by a grant from the Israeli Trauma Coalition.
Notes on contributors
Prof. Shaul Kimhi, PhD, is a full professor of psychology and head of the Master’s Studies
Program, Psychology Department, Tel Hai College, Israel.
Yohanan Eshel is an associate professor at Tel Hai College. His domains of research are
psychological resilience and educational psychology.
Mr. Dmitry Leykin, PhD, is a student at the Recanati School for Community Health Profes-
sions, Department of Emergency Medicine, Faculty of Health Sciences, Ben-Gurion University
of the Negev, Beer-Sheva, Israel. He is a head of psychology labs at Tel Hai College, Israel.
Prof. Mooli Lahad, PhD, is a full professor of psychology and drama therapy at Tel Hai
College, as well as founder and president of the Community Stress Prevention Center Kiryat
Shemona, Israel.
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