Open Journal of Psychiatry, 2011, 1, 66-74 OJPsych
doi:10.4236/ojpsych.2011.12010 Published Online July 2011 (
Published Onl ine July 2011 in SciRes.
Anger and hostility in the aftermath of a wildfire disaster in
Dimitrios Adamis1,2*, Vicky Papanikolaou3
1Research and Academic Institute of Athens, Athens, Greece;
2Institute of Psychiatry, Kings College, London, UK;
3Department of Health Service Management, National School of Public Health, Athens, Greece.
E-mail: *
Received 23 May 2011; revised 22 June 2011; accepted 1 July 2011.
Previous studies reported that anger and hostility are
often presented in the victims of a disaster. Th is study
investigates the symptoms of anger and hostility after
a wildfire disaster in a rural area of Greece. Cross
sectional case control study of adult population (18 -
65 years old). Face to face interview. Data collected
were demographic, Symptom Checklist 90-Revised
for assessment of hostility, type and number of losses,
trust in institutions personal and social attitudes. It
was found that more of the victims of the wildfires
reported symptoms of hostility compared to controls
but this difference was disappeared when we adjust
for other variables. Risk factors for development of
hostility among the victims were mistrust in military
forces and media, high levels of anxiety and distress,
younger age and having higher education. It was
concluded that anger and hostility after a disaster
perhaps are not only related to disaster but other
factors concerning demographic and personal cha-
racteristics may play an important role.
Keywords: Disaster, Greece, Hostility, Anger, Trust,
Hostility and anger have been reported as often pre-
sented in the victims of a disaster. Glass [1], in his se-
minal work has classified hostility in the last phase of a
disaster (the post-impact period). In this phase hostility
and anger appears against those possible responsible,
against society and against its leaders. [2 ].
The terms “anger” and “hostility” are often used syn-
onymously in disasters literature, but the two constructs
can be distinguished. Anger has been described as a neg-
ative feeling, an emotional state ranging from irritation
to rage; anger is an emotional expres sion of ho stility. On
the other hand hostility has been described as a general
cognitive personality trait consisting of enmity, denigra-
tion, and ill will [3-5]. Hostility is a multidimensional
trait but the two key components are cynicism, (the be-
lief that others are motivated by selfish concerns), and
mistrust, (the belief that other people will tend to be
hurtful) [5]. However there are not yet standard defini-
tions and Barefoot [6] viewed hostility as an “antagon is-
tic interpersonal attitude”, in relation to cognitions (cy-
nicism and hostile attribution s), affect (hostile emotions),
and beha vi our (aggressive ne ss).
Although ther e is a bulk of theoretical work where of-
ten has been reported that hostility and anger are com-
mon in the aftermath of a disaster there is a lack of em-
pirical evidence which examine the prevalence and the
factors contributed in the appearance of hostility in the
victims of a natural disaster [7]. This perhaps due to that
research in natural disasters is focused more on
Post-Traumatic Stress Disorder (PTSD) than other
symptoms or disorders [8,9] and also to that PTSD in-
corporates symptoms of irritability and anger. There is
evidence, however, that anger and hostility may be dis-
tinguished from other symptoms of PTSD in following a
more protracted course [10,11].
Hostility has been seen in individuals or may be col-
lective and organised and may be directed towards indi-
viduals or groups [12]. Often relief workers maybe the
focus of hostility of the victims whom they help [13],
however, recent research has showed that relief workers
also can develop elevated levels of anger and hostility
especially those with more severe symptoms of PTSD
Moreover, hostility after a disaster may have severe
implications for the recovery. Individuals with hostility
less often visited medical clinics in the aftermath of a
disaster [16], although they are in higher risk for cardi-
ovascular problems [17], they may have higher levels of
lipids in their blood, [18,19], their cortisol levels are
D. Adamis et al. / Open Journal of Psychiatry 1 (2011) 66-74
Copyright © 2011 SciRes. OJPsych
increased [20] and they are in higher risk of all-cause
mortality independently of other risk factors (e.g.,
smoking, cholesterol levels) [4,21]. In addition it has
been suggested that severity of anger and hostility is a
risk factor of family violence and substance abuse [22],
and also that is a factor for maintenance of psychological
problems and mostly PTSD [7]. On the other hand, it has
been proposed that in some cases the return of anger and
hostility can be a sign of a return to normal [23].
Besides, different kind of disaster may have a different
impact on mental health and especially in the hostility
symptom [24], and it has been suggested [8] that it is
important to distinguish continuing situations from
time-limited, acute disasters. Likewise different cause of
disasters can have impact on the development and ex-
pression of hostility and anger. Purely natural disasters
(e.g. earthquakes, tsunamis, tornados) can be seen as an
uncontrollable event or “act of God” affecting everyone,
and fate can determine who is affected. On the other
hand human made or technological disasters may evoke
more easily anger, hostility and blaming behaviour as
they due to human error or miscalculation [25-28]. Hos-
tility and anger can become dominant as victims blame
what they perceive to be the responsible agent, [25] and
they disagree over acts to stop or remediate the event or
over relief or rescue methods [25,26]. However, there is
not clear distinction of manmade and natural in the case
of wildfire disasters. Wildfires can be caused from hu-
man error or deliberately but also can be caused acci-
dentally from natural causes (lighting, weather condi-
tions) [29].
In a previous analysis of our data [30] where we ex-
amined only the psychopathology we have found that
those victims of the disaster without losses were more
hostile compared to those with losses. We had speculated
that those with d amages were in priority to receive most
of the support and so they may were less hostile. How-
ever, given that hostility is a personality trait and given
that hostility and anger can be affected by other social,
demographic, and personal attitudes, as above reported,
hostility may pre-existed the disaster and perhaps disas-
ter may exacerbated it. Similarly, other factors like per-
sonal attitudes, believes, and trust which were not ex-
amined in the previous study may influence hostility and
anger. Consequently, in the present study we hypothe-
sised that hostility after a disaster may is not only related
to the disaster but perhaps socio-demographic and per-
sonal factors contribute as well. The present study is a
post-hoc analysis of collected data after a wildfire disa s-
Therefore the aims of the present study are threefold:
a) to estimate the time prevalence of hostility symptoms
in the victims of a disaster, b) to investigate risk factors
for hostility, and c) to evaluate the associations of losses,
demographic and social factors with hostility sympt oms.
2.1. History
In August of 2007 an intense wildfire broke out in the
Peloponnesus peninsula in Greece. This was the worst of
a century in Greece. Sixty to eighty people were reported
killed and 5392 people affected from the disaster [31].
About 1500 square kilometers of forests, olive trees,
farmland, and villages were burned in these fires and the
economic damages were estimated around 1,750,000
(×1000) US$.
2.2. Design of the Study
This study was a cross sectional case control study. Cas-
es and controls were closely matched for gender, age,
educational, marital and regional distributions. The de-
sign, procedure, and the measures for this study are more
fully described in a previous study [30].
2.3. Participants
Residents aged from 18 years to 65 years old who lived
in the five prefectures designated by the Hellenic Re-
public Ministry of Interior to be disaster areas served as
cases and residents from nearby non affected areas as
controls. The number of respondents surveyed in each
prefecture was proportion al to its adult population.
2.4. Measurements
1) Demographic characteristics (age, gender, educational
background, mar ita l s ta tus, occupation).
2) Symptom Checklist 90-Revised (SCL-90-R) [32].
A Greek validated version of SCL-90-R was used [33].
The SCL-90R has 90 items, which measure the degree of
distress experienced the individual during the last 7 days,
using a 5-point scale (0 to 4) that ranges from “not at all”
to “extremely.” The SCL-90R can be scored for nine
symptom dimensions. In addition to the nine dimensions,
there are three global indices that are computed. The
Global Severity Index (GSI), which reflects both the
number of symptoms endorsed and the intensity of per-
ceived distress. The Positive Symptom Total (PST)
which is a measure of the number of symptoms endorsed
and can be interpreted as a measurement of symptoms
span, and the Positive Symptom Distress Index (PSDI),
which is a measure of “intensity” corrected for the num-
ber of symptoms. According to SCL-90-R caseness is
defined when a respondent has a GSI score greater or
equal to a T score of 63, or if any of two dimensions
scores are greater than or equal to a T score of 63.
3) Hostility: To measure hostility the 6 questions of
hostility dimension of the SCL-90-R were used. Those
D. Adamis et al. / Open Journal of Psychiatry 1 (2011) 66-74
Copyright © 2011 SciRes. OJPsych
are “feel easily annoyed or irritated”, “temper outbursts
that you cannot control”, “have urges to beat, injure or
harm somebody”, “have urges to break or to smash
things”, “have frequent arguments”, “shouting or throw-
ing things”. The hostility dimension of SCL-90-R re-
flects thoughts feelings or actions that are characteristics
of anger. The six questions of SCL-90-R asses quantities
such as aggression, irritability, rage, and resentment
4) Number and type of losses as a result of the fire in-
cluding: a) damage to property, b) complete damage and
loss of property, c) personal injury or injury of a close
family member, and d) deaths of close family members.
5) A questionnaire which examines the trust of res-
pondents in 12 institutions/ establishments/ organiza-
tions namely: Government, Church, Military, Local
government, Private sector, Trade-unions, Non Govern-
mental/Voluntary organizations, Justice, Education, Po-
lice, Political parties, and Media.
6) A questionnaire with 21 social values in which the
participants could choose which were most important for
them. Among the social values were Prestige, Devotion,
Autonomy, Ostentation of power, Mutual Help, Modesty,
Wealth, Equality, Tradition, Public recognition, Safety,
and others.
2.5. Procedure
Data were collected in face-to-face interviews conducted
during a 14-day period beginning 6 months after the
outbreak of the wildfires (March 2008). The interviewers
were qualified psychologists and social workers, who
had a previous training for the use of SCL-90-R.
Households in designated disaster areas and in the near-
by undamaged by fire areas were selected randomly
from residency data provided by the municipalities sur-
veyed. Participants were given cards upon which the
survey questions were printed. Because educational le-
vels in this region are relatively low, each question was
read out loud by the interviewer as well, who recorded
the participants’ responses.
2.6. Ethics
The study has been approved by the Ministry of Health
and informed consent was obtained from each partici-
2.7. Statistical Analy sis
The Q Local v 2.1.11, (NCS Pearson Inc, MN, USA),
was used for the estimation of the standardized T scores
from the raw data for the SCL-90-R scale. Data were
analysed with PASW (SPSS) v18, using appropriate bi-
variate statistics. For the non-normally distributed data,
non-parametric tests were used. To identify risk factors
for hostility caseness a logistic regression analysis was
3.1. Demographics
The initial sample consisted of 800 participants: 409
cases (victims from the disaster) and 391 controls. Be-
cause of missing data, uncompleted questionnaires, and
exclusion of individuals who gave the same rate (0 or 4)
in all the questions in the SCL-90-R, the final analysed
sample here consisted of 615 participants (353 cases and
262 controls). The finally analysed two groups were
closely matched regarding gender, age, education, occu-
pation and regional characteristics. (See table 1).
3.2. Caseness According to SCL-90-R
(Psychopathology Dimensions).
Those who had a T score of 63 and above in each psy-
chopathology dimension of SCL-90-R defined as case-
ness. Table 2 shows the caseness’ actual numbers and
percentages in each psychopathology dimension for cas-
es (victims) and controls.
3.2.1. Hostility
Those participants who had T scores of 63 and above in
the hostility dimension of SCL-90-R defined as hostile
(caseness). By this definition 110 participants (18%) of
the sample (N = 615) were found to have increased the
dimension of hostility (T scores 63). Using X2 tests we
compared the two populations (those with hostility and
those without) in terms of socio-demographic characte-
ristics (age, gender, marital status, occupation, educa-
tion), sampled group (controls or victims from the disas-
ter), losses (number of losses, property damages, com-
plete damages of property, injuries of self or relatives,
death of close relative), trust in institu-
tions/establishments (Government, Church, Military,
Local government, Private sector, Trade-unions, Non
Governmental/Voluntary organizations, Justice, Educa-
tion, Police, Political parties, Media), and Social values
and Personal attitudes (Dialogue/communication among
people, Stable social rules, Os tentation of power/wealth,
Autonomy, Mutual support, Modesty, Wealth, Variety,
Equality, Compliance with law, Adventure, Leisure, Na-
ture, Prestige, Creativity, Devotion, Public recognition,
Safety, Having a good time, Tradition, State). No differ-
ences were found in the two groups with the exception in
the variables showed in Table 3. Thus, victims of the
wildfire, those who did not trust the police and the jus-
tice system, and those who value more nature and leisure
but not modesty as a per- sonal value had statistically
significa nt i ncrease d the dim ens i on of hostility.
D. Adamis et al. / Open Journal of Psychiatry 1 (2011) 66-74
Copyright © 2011 SciRes. OJPsych
Table 1. Demographic characteristics of sample.
Table 2. Caseness accordi ng to SCL-90-R.
Cases N = 353(%) Controls N = 262(%)
Count Row % Count Row %
SOMATIZATION NO 290 55.3% 234 44.7%
YES 63 69.2% 28 30.8%
OBSESSIVE-COMPULSIVE (OC) NO 253 55.7% 201 44.3%
YES 100 62.1% 61 37.9%
NO 261 56.0% 205 44.0%
YES 92 61.7% 57 38.3%
DEPRESSION NO 247 53.2% 217 46.8%
YES 106 70.2% 45 29.8%
ANXIETY NO 273 55.3% 221 44.7%
YES 80 66.1% 41 33.9%
HOSTILITY NO 279 55.2% 226 44.8%
YES 74 67.3% 36 32.7%
PHOBIC ANXIETY NO 287 55.2% 233 44.8%
YES 66 69.5% 29 30.5%
PARANOID NO 228 53.1% 201 46.9%
YES 125 67.2% 61 32.8%
PSYCHOTISM NO 278 55.4% 224 44.6%
YES 75 66.4% 38 33.6%
GSI NO 250 53.8% 215 46.2%
YES 103 68.7% 47 31.3%
PSDI NO 224 56.9% 170 43.1%
YES 129 58.4% 92 41.6%
PST NO 276 54.2% 233 45.8%
YES 77 72.6% 29 27.4%
Cases N = 353(%) Controls N = 262(%) Pearson X2
Gender male 182(51.6) 131(50.0%) X2 = 0.15, df = 1, p = 0.7 (NS)
female 171(48.4) 131(50.0)
Age group
18 - 25 59(16.7) 36(13.7)
X2 = 1.32, df = 4, p = 0.86 (NS)
26 - 35 79(22.4) 59(22.5)
36 - 45 72(20.4) 59(22.5)
46 - 55 76(21.5) 55(21.0)
56 - 65 67(19.0) 53(20.2)
Primary school 101(28.6) 72(27.5)
X2 = 5.6, df = 2, p = 0.06 (NS) Secondary s chool 222(62.9) 152(58.0)
College/university 30(8.5) 38(14.5)
Marital status
married 240(68.0) 180(68.7)
X2 = 0.043, df = 3, p = 0.98 (NS)
single 99(28.0) 72(27.5)
divorced 4(1.2) 3(1.1)
windowed 10(2.8) 7(2.7)
professional occupation 59(16.7) 46(17.6)
X2 = 0.50, df = 2, p = 0. 78 ( NS)
sales and customer service
57(16.1) 47(17.9)
elementary occupation 237(67.2) 169(64.5)
D. Adamis et al. / Open Journal of Psychiatry 1 (2011) 66-74
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3.2.2. Logistic Regression. (Predictors of Hostility).
To control for the confounding variables a logistic re-
gression model were conducted with dependent variable
the hostility (outcome yes/no) and independent variables
all the above measured variables plus the psychopathol-
ogy dimensions of SCL-90-R and the three indices (GSI,
PST, PSDI). The b ackward stepwise (Wald) method was
used. The final more parsimonious model is presented in
Table 4. The final model predicts overall correctly
86.5% of participants and the prediction in creases for
those without hostility fo r whom the model classify co r-
rectly 94 % while the prediction for the hostility drops to
Thus, those of the participants who scored higher (pa-
thological) levels of hostility were those in youngerage
groups (18 - 55 years old), those who did not trust the
military forces and the media, those who had higher le-
vels of anxiety (pathological) and they had a broader and
more intensive number of symptoms (PST and PSDI).
3.2.3. Predict ors of Hostility in the Victims of the
Further we analyse only the victims of the disaster. From
the 353 victims the 74 (21%) had increased hostility.
Doing the same analysis as above on the victims’ sample
(logistic regression) we found that those hostile victims
were those who did not trust the military forces and the
media. Although overall age and education did not con-
tribute significantly to the model those in the 26 - 55
groups ages were more hostile compared to older group
age (56 - 65 years old group). Similarly with education,
overall education did not have any effect on hostility but
those with higher education (college/univ ersity), appears
to be more hostile compared to those who finished pri
mary school. As with the entire sample, victims with
increased hostility had also increased levels of anxiety
and they had more intensive and wider number of
symptoms. Tab l e 5 shows the final model with the pre-
dictive variables. The final model predicts overall cor-
rectly the 84% of the victims and for those without ho s-
tility classifies correctly the 94% while those with hos-
tility the model classifies correctly the 44.5%.
This study addresses the relationship between a natural
disaster (wildfires) and the hostility symptom of psy-
chopathology. Although, bivariate analysis showed that
the victims of the wildfires had increased hostility com-
pared to controls, after adjusting for other sociodemo-
graphic factors neither the impact of disaster nor the
losses caused by it, had any effect on the symptom of
hostility. In other words the symptom of hostility was
independent by both disaster and losses caused by the
Table 3. Hostility (Bivariat e statistics).
NO (%) YES (%) Pearson X
X2 = 5.3, df = 1, p = 0.02
Trust in Justice
X2 = 5.29, df = 1, p = 0.021
YES 40(7.9) 2(1.8)
Trust in Police
X2 = 6.23, df = 1, p = 0.013
X2 = 7.91, df = 1, p = 0.005
Nature NO 257(50.9) 38(34.5) X2 = 9.67, df = 1, p = 0.002
X2 = 4.97, df = 1, p = 0.026
Table 4. Predictors of hostility.
B S.E. Wald χ2 df Sig. Exp(B)
95% C.I.for EXP(B)
Lower Upper
Age group 14.089 4 0.007
18 - 25 1.671 0.470 12.625 1 0.000 5.316 2.115 13.359
26 - 35 1.230 0.446 7.626 1 0.006 3.423 1.429 8.196
36 - 45 1.296 0.464 7.805 1 0.005 3.654 1.472 9.069
46 - 55 1.363 0.449 9.220 1 0.002 3.908 1.621 9.422
Trust in military 1.122 0.472 5.649 1 0.017 3.071 1.217 7.744
Trust in media 1.404 0.637 4.862 1 0.027 4.071 1.169 14.178
PST –1.046 0.369 8.047 1 0.005 0.351 0.171 0.724
PSDI –1.357 0.271 25.029 1 0.000 0.257 0.151 0.438
Anxiety –2.017 0.347 33.783 1 0.000 0.133 0.067 0.263
Constant –2.165 0.836 6.703 1 0.010 0. 11 5
D. Adamis et al. / Open Journal of Psychiatry 1 (2011) 66-74
Copyright © 2011 SciRes. OJPsych
Table 5. Predictors of hostility only in the victims.
B S.E. Wald χ2 df Sig. Exp(B)
95% C.I.for EXP(B)
Lower Upper
Age group
18 - 25
26 - 35
36 - 45 1.226 0.590 4.317 1 0.038 3.407 1.072 10.830
46 - 55
Primary school
Secondary s chool
Trust in military
Trust in media
Safety –0.601 0.338 3.166 1 0.075 0.548 0.283 1.063
disaster. In addition young er age, mistrust in the military
forces and the media and high levels of anxiety and dis-
tress were predictors for the symptom of hostility. It is
important to note here that the military forces were the
most important aid for the relief of the victims but also
they had played a crucial role in the fire-fighting to stop
the catastrophic event.
Literature on exposure to other types of natural disas-
ter (floods) indicates increased hostility in the victims
[22]. Similarly, Bland [34] reported in creased hos tility in
male residents of Pozzuoli following an earthquake
compared to non-residents and further analysis showed
that hostility was more increased in those relocated and
in those victims with financial losses. In manmade dis-
asters (technological) it was reported the surprising
finding that employees in the damaged nuclear plant in
the Three Mile Island accident had lower scores on the
hostility and mistrust than other residents of the area
[35]. However, surrounding circumstances of the Three
Mile Island accident (initial failure of plant operators to
recognize the situation, and the release of the film The
China Syndrome few days before the accident) may ex-
plain this finding.
Therefore, although hostility has been observed in the
victims of a disaster other reasons may contribute as
well. The above reported studies did not control for other
factors and they found that victims are more hostile
compared to controls (like in the present study, when
bivariate analysis was used). However, a study of survi-
vors of the Beverly Hills Supper Club fire of 1977
(Green [36]) in which regression analysis was used, re-
ported that hostility was predicted from the stress caused
by the fire and demographic factors (particularly age).
Although direct comparison of Green et al.’s study with
the present one is difficult, because of the different type
of disaster, different methodology, and different meas-
ured variables, the Green et al study further supports the
indication that hostility and perhaps other symptoms of
psychopathology are not only related to victim/control
distinction, but they may related also to other factors
concerning social and personal attitudes. Similarly, emo-
tional and psychological support, supportive network,
close family ties may influence the outcome of trauma.
However, it is important to consider both the positive
and negative consequences of social involvement be-
cause it was found for instance that spouse support may
reduce male symptomatology but this is associated with
increased symptomatology in exposed to disaster fe-
males. Very strong social ties may be more burdensome
than supportive in extreme stress [37]. Nevertheless,
including other variables such as social may add more to
predictive outcome than a simple comparison of vic-
tims/controls psychopathology or distress.
It has been argued that manmade disasters are pheno-
menologically and etiologically different from natural
disasters [38], and as above reported wildfires some-
times can be in the middle. During the time of wildfires
in Greece there was a political campaign for the national
election. There was a suspiciousness that the fires might
have been set by political extremists, to disrupt political
campaign. This suspiciousness was not only among
laymen but also the Prime Minister in a nationally tele-
vised address suggested it. [39]. Media spread it as well
[40], but six months later when this study was carried
D. Adamis et al. / Open Journal of Psychiatry 1 (2011) 66-74
Copyright © 2011 SciRes. OJPsych
out nobody has been held responsible. This could ex-
plain to some degree the mistrust to the media.
However, general the lack of trust has also been re-
ported in other studies investigating victims of disaster
e.g. [41]. Previous studies have showed that trust is es-
sential component of resilience, and individuals and
communities can effectively respond to a disaster by
gathering together trust, and social support, to either
re-establish a previous state of equilibrium or develop a
different but still adaptive state e.g. [42-46].
A previous study has shown that Greeks have a low
level of trust in the most public institutions [47]. Simi-
larly, a more recent survey on younger Greek population
(18 to 28 years old) also reported a low trust in public
institutions and politics. In addition, the same survey
reported that more than half (53%) of the Greek young
people are unconcerned about others and only 21.5%
trust others to some degree [48].
Mistrust and a negative attitude toward others are es-
sential components to hostility [49]. Thus, it is very
likely that in both cases and controls the mistrust and the
negative attitude pre-existed to the disaster and so we do
not find any effect from the disaster because it was con-
founded with pre-disaster attitudes. Alternatively, if the
disaster had provoked mistrusts and disbelief to others
we should find that victims were more hostile than con-
trols. In addition to our hypothesis that hostility
pre-exists to disaster is that hostility is rather a personal-
ity trait and an attitude that may be derived from nega-
tive interpersonal experiences and thus it is more likely
to be a long standing symptom rather than a symptom
caused instantly after the disaster [50]. Moreover, bio-
logical (serotonergic system) and genetic factors regulate
so many of the behavioural and psychosocial characte-
ristics. Research on genes has focused on variants in
genes encoding for proteins involved in the regulation of
serotonergic function. It is suggested that the serotonin
1B receptor gene play an important role in phenotypes of
personality domains related to anger and hostility
A rather surprising finding of this study was that hos-
tility in the victims of wildfire was associated with high-
er education. Generally educated people report less hos-
tility and anger toward others but when worried, anxious,
or tense, they are more likely to report anger along with
it [53]. A previous study of explosive anger in
post-conflict victims showed that among others, higher
levels of education is negatively associated with anger
[11]. However, not all the studies in d isasters hav e found
that education has a protective effect on hostility e.g.
among survivors of the Oakland/Berkeley firestorm [54],
on individuals exposed to a flood in South Africa [55].
There is no obvious explanation for this finding. A spec-
ulation is this suggested by Gibbs [56]. Considering that
higher education is associated with higher income and
possible higher social class when those individu als were
equally affected by disaster as lower class individuals, it
may be that higher social class individuals have more to
lose in the disaster. Their expectations and the standards
of living may be higher and more crudely disrupted than
the expectations of lower class or less educated individ-
uals. Although, in the present study, we did not find any
effect of the type or the number of losses in the hostility
dimension, it is possible that more educated people may
have greater expectations than less educated, and thus
they are perhaps more hostile than the less educated. A
second possibility is that hostility effects of a traumatic
experience may affect more those educated who may
have more pressure and responsibilities compare to oth-
ers and perhaps take also responsibilities for other
non-educated people.
4.1 Limitations of the Study
Culture and milieu may have influenced the relationship
of hostility and victims of the wildfire disas ter. Although
SCL-90-R estimate psychopathology based in the last 2
weeks there is possibility of recall bias or influences in
the other measurements as well, since the study was
conducted 6 months after disaster. We did not use other
measures of hostility. However, SCL-90-R is a good
measurement of hostility as it evaluates hostility as a
spectrum from anger to aggression.
[1] Glass, A.J. (1959) Psychological aspects of disaster.
Journal of American Medical Association, 171, 222-225.
[2] McGonagle, L.C. (1964) Psychological Aspects of Dis-
aster. American Journal of Public Health and the Na-
tions Health, 54, 638-643. doi:10.2105/AJPH.54.4.638
[3] Spielberger, C.D., Jacobs, G., Russell, S.F. and Crane,
R.S. (1983) Assessment of anger: The state-trait anger
scale. In: Butcher, J.N. and Spielberger, C.D. Eds., Ad-
vances in Personality Assessment, Erlbaum , Hillside.
[4] Smith, T.W., Glazer, K., Ruiz, J.M. and Gallo, L.C. (2004)
Hostility, anger, aggressiveness, and coronary heart dis-
ease: An interpersonal perspective on personality, emo-
tion, and health. Journal of Personality, 72, 1217-1270.
[5] Powell, L.H. and Williams, K. (2007) Hostility. In: Fink,
M.G. Eds., Encyclopedia of Stress, Academic Press, New
York, 354-358.
[6] Barefoot, J.C., Dodge, K.A., Peterson, B.L., Dahlstrom,
W.G. and Williams, R.B.Jr. (1989) The Cook-Medley
hostility scale: Item content and ability to predict surviv-
al. Psychosomatic Medicine, 51, 46-57.
[7] Jayasinghe, N., Giosan, C., Evans, S., Spielman, L., and
Difede, J. (2008) Anger and posttraumatic stress disorder
in disaster relief workers exposed to the September 11,
2001 World Trade Center disaster: One-year follow-up
D. Adamis et al. / Open Journal of Psychiatry 1 (2011) 66-74
Copyright © 2011 SciRes. OJPsych
study. The Journal of Nervous and Mental Disease, 196,
844-846. doi:10.1097/NMD.0b013e31818b492c
[8] Weiss, M.G., Saraceno, B., Saxena, S. and van Ommeren,
M. (2003) Mental health in the aftermath of disasters:
Consensus and controversy. The Journal of Nervous and
Mental Disease, 191, 611 -615.
[9] Hussain, A., Weisaeth, L. and Heir, T. (2010) Psychiatric
disorders and functional impairment among disaster vic-
tims after exposure to a natural disaster: A population
based study. Journal of Af fective Disorders, 128, 135-141.
[10] Orth, U., Cahill, S.P., Foa, E.B. and Maercker, A. (2008)
Anger and posttraumatic stress disorder symptoms in
crime victims: A longitudinal analysis. Journal of Con-
sulting and Clinical Psychology, 76, 208-218.
[11] Silove, D., Brooks, R., Steel, C.R.B., Steel, Z., Hewage,
K., Rodger, J. and Soosay, I. (2009) Explosive anger as a
response to human rights violations in post-conflict Ti-
mor-Leste. Social Science & Medicine, 69, 670-677.
[12] Edwards, J.G. (1976) Psychiatric aspects of civilian dis-
asters. British Medical Journal, 1, 944-947.
[13] I. Palmer. (2005) ABC of conflict and disaster. Psycho-
logical aspects of providing medical humanitarian aid.
British Medical Journal, 331, 152-154.
[14] Ursano, R.J., Fullerton, C.S., Kao, T.C. and Bhartiya, V.R.
(1995) Longitudinal assessment of posttraumatic stress
disorder and depression after exposure to traumatic death.
The Journal of Nervous and Mental Disease, 183, 36-42.
[15] Evans, S., Giosan, C., Patt, I., Spielman, L. and Difede, J.
(2006) Anger and its association to distress and so-
cial/occupational functioning in symptomatic disaster re-
lief workers responding to the September 11, 2001,
World Trade Center disaster. Journal of Traumatic Stress,
19, 147-152. doi:10.1002/jts.20107
[16] Donker, G.A., van der Velden, P.G., Kerssens, J.J. and
Yzermans, C.J. (2008) Infrequent attendance in general
practice after a major disaster: A problem? A longitudinal
study using medical records and self-reported distress
and functioning. Family Pr actice, 25, 92-97.
[17] Beckham, J.C., Flood, A.M., Dennis, M.F. and Calhoun,
P.S. (2009) Ambulatory cardiovascular activity and hos-
tility ratings in women with chronic posttraumatic stress
disorder. Biological P sychiatry, 65, 268-272.
[18] Brindley, D.N., McCann, B.S ., Niaura, R., Stoney, C.M.
and Suarez, E.C. (1993) Stress and lipoprotein metabol-
ism: Modulators and mechanisms. Metabolism, 42, 3-15.
[19] Lane, J.D., Pieper C.F., Barefoot J.C., Williams, R.B.Jr.
and Siegler, I.C. (1994) Caffeine and cholesterol: Interac-
tions with hostility. Psychosomatic Medicine, 56, 260-266.
[20] Wang, H.H., Zhang, Z.J., Tan, Q.R., Yin, H., Chen, Y.C.,
Wang, H.N., Zhang, R.G., Wang, Z.Z., Guo, L., Ta ng,
L.H. and Li. L.J. (2010) Psychopathological, biological,
and neuroimaging characterization of posttraumatic
stress disorder in survivors of a severe coalmining disas-
ter in China. Journal of Psychiatric Research, 44, 385-392.
[21] Zhang, J., Niaura, R., Todaro, J.F., McCaffery, J.M. and
Shen, B.J., Spiro, A. and Ward, K.D. (2005) Suppressed
hostility predicted hypertension incidence among mid-
dle-aged men: The normative aging study. Journal of
Behavioral Medicine, 28, 443-454.
[22] Clemens, P., Hietala, J.R., Ry tter, M.J., Schmidt, R.A.
and Reese, D.J. (1999) Risk of domestic violence after
flood impact: Effects of social support, age, and history
of domestic violence. Applied Behavi oral Sc ienc e Rev ie w,
7, 199-206. doi:10.1016/S1068-8595(00)80020-3
[23] Ursano, J.R., Fullerton, S.C. and Benedek, M.D. (2009)
What is Psychopathology after Disasters? Considerations
about the nature of the psychological and behavioral
consequences of disasters in mental health and disasters.
In: Neria, Y., Galea, S. and Norris, F.H. Eds., Mental
Health and Disasters, Cambridge University Press,
Cambridge, 131-145.
[24] Norris, F.H., Friedman, M.J. and Watson, P.J. (2002)
60,000 disaster victims speak: Part II. Summary and im-
plications of the disaster mental health research. Psy-
chiatry, 65, 240-260. doi:10.1521/psyc.
[25] Cuthbertson, B.J. and Nigg, J.M. (1987) Technological
disaster and the nontherapeutic community: A question of
true victimization. Envir onmen t and Beha vior, 19, 462-483.
[26] Kroll-Smith and J.S. and Couch, S. (1990) The real dis-
aster is above ground: A mine fire and social conflict.
University of Kentucky Press, Lexington.
[27] Quarantelli, E., Dynes, R.R. (1976) Community conflict:
Its absence and its presence in natural disasters. Mass
Emergencies, 1, 139-156.
[28] Havenaar, J.M. and Rumyantzeva, G.M., van den Brink,
W., Poelijoe, N.W., van den Bout J., van Engeland, H.
and Koeter, M.W. (1997) Long-term mental health ef-
fects of the Chernobyl disaster: An epidemiologic survey
in two former Soviet regions. The American Journal of
Psychiatry, 154, 1605-1607.
[29] Taylor, A.J. (1987) A taxonomy of disasters and their
victims. Journal of Psychosomatic Research, 31, 535-544.
[30] Papanikolaou, V., Adamis, D., Mellon, R.C. and Prodro-
mitis, G. (2011) Psychological distress following wild-
fires disaster in a rural part of Greece: A case-control
population-based study. International Journal of Emer-
gency Mental Health, in press.
[31] EM-DAT. (2008) The OFDA/CRED International Disas-
ter Database Prevention
[32] Derogatis, L.R. (1992) SCL-90-R: Administration, scor-
ing & procedures manual-II, for the (revised) version and
other instruments of the psychopathology rating scale se-
ries. 2nd Edition, Clinical Psychometric Research, Tow-
[33] Donias, S., Karastergiou, A. and Manos, N. (1991) Stan-
dardization of the Symptom Checklist 90 rating scale in a
Greek population. Psychiatriki, 2, 42-48.
[34] Bland, S.H., O’Leary, E.S., Farinaro, E., Jossa, F. and
Tr e visanm, M. (1996) Long-term psychological effects
of natural disasters. Psychosomatic Medicine, 58, 18-24.
D. Adamis et al. / Open Journal of Psychiatry 1 (2011) 66-74
Copyright © 2011 SciRes. OJPsych
[35] Chisholm, R.F., Kasl, S.V., Dohrenwend, B.P., Dohren-
wend, B.S., Warheit, G.J., Goldsteen, R.L., Goldsteen, K.
and Martin, J.L. (1981) Behavioral and mental health ef-
fects of the three mile island accident on nuclear workers:
A preliminary report. Annals of the New York Academy of
Sciences, 365, 134-135.
[36] Green, B.L., Grace, M.C. and Gleser, G.C. (1985) Iden-
tifying survivors at risk: Long-term impairment follow-
ing the Beverly Hills Supper Club fire. Journal of Con-
sulting and Clinical Psychology, 53, 672-678.
[37] Solomon, S.D ., Smith, E.M., Robins, N.L. and Fischbach,
R.L. (1987) Social Involvement as a Mediator of Disas-
ter-Induced Stress. Journal of Applied Social Psychology,
17, 1092-1112. doi:10.1111/j.1559-1816.1987.tb02349.x
[38] Green, B.L., Lindy, J.D. and Grace, M.C. (1995) Psy-
chological effects of toxic contamination. In: Ursano,
R.J., McCaughey, B.G., Fullerton, C.S. Eds., Individual
and Community Responses to Trauma and Disaster: The
Structure of Human Chaos, Cambridge University Press,
[39] CNN (2007) Greek leader suggests political extremists
set fires.
fire-victims -t op-fire-offici al-pel.
[40] M. Nodaros (2007) Land of Death Eleftherotypia, Tego-
[41] Quinn, S.C. (2006) Hurricane Katrina: A social and pub-
lic health disaster. American Journal of Public Health, 96,
204. doi:10.2105/AJPH.2005.080119
[42] Rolfe, R.E. (2006) Social cohesion and community resi-
lience: A multidisciplinary review of literature for rural
health research. Department of International Develop-
ment Studies Faculty of Graduate Studies and Research
Saint Mary’s University, Halifax.
[43] Schellong, A., Wolfgang, J. and Main, F. A. (2007) In-
creasing social capital for disaster response through so-
cial networking services (SNS) in Japanese Local Gov-
ernments. Harvard University, Cambridge.
[44] Sakamoto, M. and Yamor y, K. (2009) A Study of life
recovery and social capital regarding disaster victims–A
case study of Indian ocean tsunami and central java
earthquake recovery. Journal of Natural Disaster Science,
21, 13-20.
[45] Paton, D., Houghto n, B.F., Gregg, C.E., McIvo r, D., Johns-
ton, D.M., Burgelt, P., Larin, P., Gill, D.A., Ritchie, L.A.,
Meinhold, S. and Horan, J. (2009) Managing Tsunami
risk: Social context influences on Preparedness. Journal
of Pacific Rim Psychology, 3, 27-37.
[46] Kirmay er, J.L., Sehdev, M., Whitley, R., Dandeneau, F.S.
and Isaac, C. (2009) Community resilience: Models, me-
taphors and measures. Journal of Aboriginal Health, 5,
[47] Lyberaki, A. and Paraskevopoulos, J.C. (2002) Social
capital measurement in Greece. Paper presented at the
International Conference on Social Capital Measurement.
[48] Papadimitriou, V. (2007) Family is a supporting system
for the 60% of young people. Apogeumatini tis Kyriakis,
Athens, 18-19.
[49] Schulman, J.K. and Stromberg. S. (2007) On the value of
doing nothing: Anger and cardiovascular disease in clin-
ical practice. Cardiology Review, 15, 123-132.
[50] Berkowitz, L. (1993) Aggression: Its causes, conse-
quences, and control. Temple University Press, Philadel-
[51] Lesch, K.P., Bengel, D., Heils, A., Sabol, S.Z., Greenberg,
B.D., Petri, S., Benjamin, J., Muller, C.R., Hamer, D.H.
and Murphy, D.L. (1996) Association of anxiety-related
traits with a polymorphism in the serotonin transporter
gene regulatory region. Science, 274, 1527-1531.
[52] Conner, T.S., Jensen, K.P., Tennen, H., Furneaux, H.M.,
Kranzler, H.R. and Covault, J. (2010) Functional poly-
morphisms in the serotonin 1B receptor gene (HTR1B)
predict self-reported anger and hostility among young
men. American Journal of Medical Genetics part B:
Neuropsychiatric Genetic, 153B, 67-78.
[53] Mirowsky, J. and Ross, C.E. (2007) Education levels and
stress. In: Fink M.G. Ed., Encyclopedia of Stress, Aca-
demic Press, New York, 888-892.
[54] North, C.S., Hong, B.A., Suris, A. and Spitznagel, E.L.
(2008) Distinguishing distress and psychopathology among
survivors of the Oakland/Berkeley firestorm. Psychiatry,
71, 35-45. doi:10.1080/00224545.1970.9919957
[55] Strumpfer, D.J. (1970) Fear and affiliation during a dis-
aster. Journal of Social Psychology, 82, 263-268.
[56] Gibbs, M.S. (1989) Factors in the victim that mediate
between disaster and psychopathology: A review. Journal
of Traum atic Stre ss, 2, 489-514.
doi: 10.1007/BF00974604