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Sci Eng Ethics (2014) 20:717–733
DOI 10.1007/s11948-013-9502-z
ORIGINAL PAPER
Social Media in Disaster Risk Reduction and Crisis
Management
David E. Alexander
Received: 24 April 2013 / Accepted: 27 November 2013 / Published online: 4 December 2013
Springer Science+Business Media Dordrecht 2013
Abstract This paper reviews the actual and potential use of social media in
emergency, disaster and crisis situations. This is a field that has generated intense
interest. It is characterised by a burgeoning but small and very recent literature. In
the emergencies field, social media (blogs, messaging, sites such as Facebook, wikis
and so on) are used in seven different ways: listening to public debate, monitoring
situations, extending emergency response and management, crowd-sourcing and
collaborative development, creating social cohesion, furthering causes (including
charitable donation) and enhancing research. Appreciation of the positive side of
social media is balanced by their potential for negative developments, such as
disseminating rumours, undermining authority and promoting terrorist acts. This
leads to an examination of the ethics of social media usage in crisis situations.
Despite some clearly identifiable risks, for example regarding the violation of privacy, it appears that public consensus on ethics will tend to override unscrupulous
attempts to subvert the media. Moreover, social media are a robust means of
exposing corruption and malpractice. In synthesis, the widespread adoption and use
of social media by members of the public throughout the world heralds a new age in
which it is imperative that emergency managers adapt their working practices to the
challenge and potential of this development. At the same time, they must heed the
ethical warnings and ensure that social media are not abused or misused when crises
and emergencies occur.
Keywords Social media Disasters Emergency management Ethics
Twitter Facebook
D. E. Alexander (&)
Institute for Risk and Disaster Reduction, University College London, Gower Street,
London WC1E 6BT, UK
e-mail: david.alexander@ucl.ac.uk
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Introduction and Definitions
At 09:02, local time, on 29th May 2012, a damaging earthquake struck EmiliaRomagna and Lombardy regions of northern Italy. This was the second major
seismic event to affect the area in 10 days. It killed 17 people and caused extensive
damage to 40 municipalities. Within 50 minutes a clear and relatively comprehensive picture of the earthquake and some of its most important impacts was available.
It could be consulted via the Internet from almost anywhere in the world. The
information presented was essentially accurate and the speed with which it became
available was largely a result of the use of social media to communicate from the
sites affected to places where data could be collected and presented to the public.
The term ‘social media’ embraces blogs, micro-blogs, social book-marking,
social networking, forums, collaborative creation of documents (via wikis1) and the
sharing of audio, photographic and video files (Balana 2012). It is characterised by
interactive communication, in which message content is exchanged between
individuals, audiences, organisations and sectors of the general public.
Social media usage is, to some extent, negatively correlated with age and
positively with educational attainment. For example, people over the age of 55 tend
to prefer conventional sources of news. The degree of adoption of social media
varies from country to country but is generally dynamic in most environments and
hence any summary statistics are liable to become outdated rapidly. Attempts to
relate social media to personality factors have suggested that they are most
attractive to people, of both sexes, who are relatively extrovert (Correa et al. 2010),
but there is no indication of the extent to which any effort to develop profiles of
users might be culturally conditioned. Information on gender differentiation is, at
best, fragmentary (Armstrong and McAdams 2009).
In the United States, the Internet is the most important source of information
for people under the age of 30. For other Americans, it is second only to
television (Krimsky 2007). Elsewhere, the use of ‘smart’ phones and social media
resources is increasing so rapidly that they are now a force to be reckoned with
throughout the world. Social media dispense with ‘‘information gatekeepers’’,
which include doctors giving on-line medical advice and journalists relating a
news story. These figures are replaced by apomediaries, in which network filtering
or group moderation are the only processes by which the spontaneous feed of
information is regulated—a matter of apomediation or disintermediation (Eysenbach 2008).
This paper offers a review of the use of social media in disasters and major
incidents. I consider both how citizens, emergency managers and first responders
make use of social media in crisis and how researchers perceive and characterise the
phenomenon. I examine seven ways in which social media are put to use for disaster
response, recovery and risk reduction. As social media have both beneficial and
potentially malign connotations, their advantages and drawbacks are discussed.
Next, I consider the ethical implications of social media in disaster, including the
1
The term ‘wiki’ is defined by the OED as ‘‘A type of web page designed so that its content can be edited
by anyone who accesses it, using a simplified markup language.’’ It was apparently first used in 1995.
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risks and dilemmas of unregulated communication and the degree of inclusiveness
of new media. In order to end on a positive note, examples of successes with social
media in disaster are briefly discussed. Finally, some conclusions are drawn, but
these must necessarily be provisional, as the field is in the early stages of rapid
evolution in relation to both technological development and social acceptance.
The Research Literature
The research literature on social networking and social media in disasters and crises
is still quite limited. Moreover, it focuses on the short-term aspects of emergency
response and rapid recovery. It is understandable that there are as yet no studies of
the longer term, both because social media are a relatively new phenomenon and
because the research is also new. Although ‘new media’, such as the Internet, have
received attention from academics for a decade or more, very little of the research
on social networking predates 2007. However, there is a trend towards a rapid
increase in the number of papers that have been published. In this context, the
literature on ‘social media’ needs to be differentiated from that on the social aspects
of mass media, which is a much wider field that embraces more conventional and
long-standing forms of dissemination of information, such as radio and television
(Quarantelli 1989).
Studies of social media in disasters have been conducted as part of a general
tendency to examine the functioning of social interaction by means of the Internet
and mobile devices (Krimsky 2007). Both sets of literature concentrate mainly on
specific themes, which are:
•
•
•
•
how social networks function and how they are used
how to build and utilise algorithms either to enhance social networking or to
monitor it
the extent to which people use social networks, how they perceive them and
what their communication preferences are
the penetration of devices such as ‘smart’ mobile telephones and the extent to
which these provide people with access to social media.
In addition, students of risk, crisis and disaster have studied:
•
•
•
how social media are used in crises
the views and opinions of emergency managers and journalists regarding social
media and the extent to which the new media are integrated with more
traditional means of communication
how social media interact with the traditional sources of information.
There is a broad distinction between studies of the technical and social aspects of
new media. The creation of new platforms and algorithms characterises the former
(Cheong and Lee 2010; White and Plotnik 2010), while studies of the kinds of usage
and messages sent relate to the latter (Hughes and Palen 2009; Lindsay 2011). The
technical side includes by studies of the rate and modality of diffusion of messages
(Song and Yan 2012).
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While researchers work to develop software for the efficient dissemination of
messages via social networks during crisis situations (e.g. Plotnick et al. 2009),
Reuter et al. (2012) advocated a more systematic approach to the use of social
networking software in crisis situations, starting with classification of uses and
potentials.
Researchers are equivocal about the balance between the advantages and
drawbacks of social media (see below), but they are united in identifying the uses to
which the media can be put. Social media promote cross-platform accessibility and a
constant flow of information. Situational updates can be complemented by
geographical and locational data (Vieweg et al. 2010). Just-in-time information
can be provided on how to cope with developing situations. Moreover, social media
provide a framework for the work of journalists and for public discussion and debate.
Social Media in Disaster and Crisis
The following are some of the ways in which social media can be used in disaster
risk reduction and crisis response.
1.
A listening function. Social media are able to give a voice to people who do not
normally have one. They also enable a remarkably democratic form of
participation in public debate and facilitate the exchange of information and
points of view. During an emergency, through their tendency to coalesce
opinions (or stimulate monetary donations), social media are capable of
revealing some aspects of the mental and emotional state of a nation. This may
seem a rather exaggerated claim, but it should be noted that Quarantelli (1997)
argued that the advent of modern information and communications technology
involves changes that are as profound as those that occurred after the invention
of printing. These changes do, or soon will, affect directly the majority of the
population and the rest indirectly.
The listening function involves constantly or periodically sampling the varied
output of social media. This enables currents of popular opinion and public
preference to be gauged. It may also indicate how the public is behaving and
reacting to events. Crawford (2009) classified online listening into three categories:
background listening, reciprocal listening and delegated listening by corporations.
Crawford defined background listening as mere tuning in, a minimal form of
engagement. Reciprocal listening involves two-way exchange of messages, with
mutual sensitivity to their content and implications; and delegated listening is a
form of ‘‘arm’s length engagement’’, in which messages are monitored and
responded to, if at all, en masse. Hence, listening is a question of keeping track of
opinions, giving advice or collecting information that is of interest to corporations.
As Crawford (2009, p. 526) noted, ‘‘there has been a glorification of ‘voice’ as the
prime form of participation online.’’
2.
Monitoring a situation. Whereas the listening function involves the passive
collection of information, monitoring is conducted in order to improve reactions
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to events and better to manage the general public by learning what people are
thinking and doing. Current research (Bird et al. 2012) suggests that harmful
and inaccurate rumours are not particularly enhanced by the use of social
media. One reason for this is that, with mass participation, the false rumours
that do begin to circulate are easily corrected by knowledgeable people. Hence,
in the aftermath of the Japanese earthquake and tsunami of March 2011, there
was little indication that the massive use of social media by the Japanese public
led to the successful propagation of rumour and wildly incorrect information
(Hjorth and Kim 2011). Moreover, Stirratt (2011) found that, in the Japan
disaster, 49 % of Twitter messages were either positive or somewhat positive in
their attitude to emergency preparedness and only 7 % were negative.
Floods in Queensland, Australia, led to extensive use of social media for public
interaction and communication, but not for the mass propagation of false
information. Bird et al. (2012, pp. 30–31) noted that: ‘‘While rumours were
common at the height of the disaster, respondents reported that the moderators of
the Facebook pages were prompt at confirming information and providing official
sources when available.’’ Hence, despite the presence of a major crisis—the
floods—the use of social media did not lead to a situation of general anarchy that
was out of control.
3.
Integration of social media into emergency planning and crisis management. In
a questionnaire survey (Barr 2011), it was found that 80 % of US general public
and 69 % of online users felt that it would be beneficial for national emergency
response organisers to monitor social networking sites regularly. However, in
most places this has not happened. Agencies are afraid that social networks will
produce inaccurate information of dubious provenance (Goolsby 2010).
Moreover, the full integration of social networks into disaster management
would require many of them to change their working practices, as, in the words
of Palen et al. (2007), ‘‘command-and-control models do not easily adapt to the
expanding data-generating and data-seeking activities by the public.’’ Nonetheless, there is immense potential to make data dissemination a two-way
process, in which information is both received from the public and fed to it
(Crowe 2012; Jennex 2012a; Sykes and Travis 2012).
The assertion that command and control may be at odds with social media
deserves further elaboration. I have argued elsewhere (Alexander 2008) that there is
a continuum between command-based and collaborative models of emergency
management. The command end of the spectrum tends to be authoritarian, and to
divide competencies by level of command into strategic, tactical and operational.
The collaborative end of the spectrum tends to divide competencies by theme, such
as communication, logistics, and shelter. As there is no clear hierarchical structure
in social media, they fit much better into a collaborative model than a command one.
Present experience suggests (Yates and Paquette 2011) that issuing orders to the
general public is likely to generate an adverse reaction on social media, whereas
issuing requests for collaboration may elicit a more positive response, based on
involvement rather than alienation. Moreover, the thematic organisation of
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collaborative models of emergency management favour collective information
sharing on tasks, topics and sectors.
Hughes and Palen (2012) observed that the strict bureaucratic nature of
emergency management systems, such as the US NIMS, is at variance with the open
system and free access character of the social media of which emergency managers
are being exhorted to make use. However, the direct, person to person nature of
social media is a boon to public information officers, as it helps them avoid the
common pitfall of being misquoted by the official media. Moreover, citizens are
widely recognised to be the real first responders after disaster (Helsloot and
Ruitenberg 2004): they hold the key to the use of social media as an extension of
emergency management. Rarely are emergency management organisations ready to
utilise such developments. As Westbrook et al. (2012, p. 2) observed, ‘‘The
community, volunteer organizations, and news organizations are currently embracing social media, but EM is slow to adopt and implement it on a full scale.’’ There
are demonstrable benefits from doing so. For example, Vihalemm et al. (2012)
found that social media can help citizens receive, understand and cope emotionally
with warning messages.
Yet there is an imperative to act: the public can now share information and
disseminate critical news to the world and each other without going through
government communication methods. This is revolutionizing the way in which
people seek help and the way first responders and managers receive and exchange
information. The very structure of communication and information sharing
dynamics is changing for both for emergency managers and the public. As the
Director of the US. Federal Emergency Management Agency, Craig Fugate, stated
in a Senate Homeland Security Hearing in 2011, one of the social elements that is
changing in the field of emergency management is the way the public can now be
viewed ‘‘as a resource and not a liability.’’ For example, social media can be used to
deliver warnings to users. In the most sophisticated cases, these may involve local
information in the form of maps and data, as well as instructions on what to do
during an impending crisis.
4.
Crowd-sourcing and collaborative development. In most disasters, the first
responders are the public. Moreover, social capital is involved in the form of
the mobilisation of skills, leadership, networks, support systems, and so on
(Dufty 2012). This involves the concept that social networks and interaction
between people increase productivity and lend added value to outcomes. The
social networks benefit from the particular skills of their members. One aspect
of the formation of social capital through social media is crowd-sourcing. For
example, Ushahidi is the name of a crowd-sourced crisis mapping platform
(www.ushahidi.com—Gao et al. 2011a). Sahana, and its derivatives Eden,
Vesuvius and Mayon, are open source disaster management systems. These
initiatives rely on spontaneous contributions to make them work. This endows
them with positive feedback, in that the more they are used, the more popular
they become and the more they encourage users to contribute to them. Ushahidi
and Sahana are examples of the use of social media to create and disseminate
methods and good practices, and to form social capital. They are open-source,
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free-access platforms that can be used and modified by anyone. In this respect,
they are particularly useful for places where disaster management and response
are poorly developed and resources are scarce.
In crowd-sourcing, it is suggested that 1 % of the crowd will create content, 10 %
will validate it and 89 % will use it (Goolsby 2010). However, this is sufficient to
maintain a constant flux of information and a high level of consultation of the sites
built upon crowd-sourcing. The drawbacks are that crowd-sourcing lacks a common
mechanism to facilitate coordination between organisations, it lacks security
features, and it does not necessarily provide the information that is most needed or
most accurate (Hammon and Hippner 2012). Nevertheless, crisis mapping is
particularly suited to crowd-sourcing through the use of social networks, in that
reports can be received from many users, and compiled into the resultant maps,
which can be widely disseminated. Maps can depict survivors’ temporary settlement
camps, resource distribution sources, accessible roads, impacted areas, and so on. In
the words of one researcher (Goolsby 2009), crowd-sourcing creates a sort of ‘‘open
intranet’’ in relation to the Internet, or in other words a community of users.
5.
Creating social cohesion and promoting therapeutic initiatives. Social media
can be used to make people feel part of particular initiatives. They can foster a
sense of identification with local or on-line communities. Researchers (e.g.
Taylor et al. 2012, p. 25) have noted that people caught up in disaster reported
feeling more supported and more optimistic about the future when social media
were extensively involved. Moreover, social media can be used to enhance
voluntarism by increasing the profile and connectedness of voluntary organisations. In this way, they can have a positive impact on the esprit de corps of
the members.
An American Red Cross survey of social media usage was carried out in 2010
(Blanchard et al. 2010). It indicated that 24 % of the US population and 31 % of the
online population would use the media to tell family and friends they are safe. This
reflects both the utility of social media and a well-founded lack of confidence in
means of communication such as direct telephone calls, which are subject to
network saturation.
6.
7.
The furtherance of causes. Social media such as Twitter can be used to launch
an appeal for donations. With respect to the 2010 Haiti earthquake disaster,
Lobb et al. (2012) found that television had a much greater impact in this
respect, but nevertheless a Twitter appeal did elicit a considerable response
from public donors. Gao et al. (2011b) found that In 48 hours the American Red
Cross received $8 million in donations merely from text messages. Lobb et al.
(2012) observed a rapid rise in donations straight after the disaster, when news
coverage was maintained at a high level, and then a gradual, persistent decline
as coverage dwindled and disappeared.
Research. The understanding of social reactions to stress, risk and disaster can
be enhanced by the use of social media. This represents a challenge to
researchers, who are struggling to create what one of them has called a ‘‘digital
ethnography’’ (Murthy 2011a). Some authors (e.g. Castillo et al. 2011) have
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chronicled the move towards automatic credibility analysis. Others have
compared activity on social media sites with the timeline of events in the field
(Chung 2011).
The Negative Side of Social Media
Reported above are seven ways in which social media are useful and through which
they show promise for development in the fields of disaster response and resiliency.
However, they do have a darker side (Chung 2011; CSS-ETH 2013). Rumour
propagation is not to be ruled out, nor is the dissemination of false or misleading
information, whether this is done inadvertently or deliberately. Anyone who doubts
the power of Internet-based information to disseminate false information should
type the words ‘‘earthquake prediction’’ into a search engine. The resulting sites are
a mixture of those that purvey dispassionate scientific information and those that are
based on highly debatable, perhaps utterly unscientific, premises and methodologies. Yet the sites run by charlatans often have the same visual impact, and thus
superficial legitimacy, as the authoritative scientific sites (Flanagin and Metzger
2007). Worse still, potentially social media can be used to orchestrate crime,
depending on the strength or weakness of any function that arises, probably quite
spontaneously, to ‘‘self-police’’ their output (Goolsby 2010).
Castillo et al. (2011, p. 675) observed that ‘‘immediately after the 2010
earthquake in Chile, when information from official sources was scarce, several
rumours posted and re-posted on Twitter contributed to increase the sense of chaos
and insecurity in the local population.’’ This contradicts the rumour-quelling
propensity of social media recorded in Tokyo after the 2011 earthquake (Bird et al.
2012). Castillo et al. (2011) also found that people had more faith in traditional
media, and headlines on Twitter were regarded as less credible. Twitter was seen as
a tool for political and commercial propaganda. Moreover, these authors found that
outbursts of public sentiment correlated with unreliability in Twitter messages.
They attributed some of the drawbacks of Twitter to the disconnection between online messages and the reality on the ground, which the message writers had
difficulty in assessing properly.
One event in mid-2013 illustrates the negative effect that social media can have
during a major incident. In the night of 4 May 2013 a freight train derailed at
Wetteren near the Belgian city of Ghent, releasing acrylonitrile gas in an explosion
and toxic cloud. Concentrations of the gas reached 600 parts per million, which is
6–8 times the lethal dose. One person died and 93 were injured by the fumes. As the
area that was affected is densely urbanised, many aspects of this major incident
were shared on social media. However, according to the commander of the Ghent
Fire Brigade (GFB), Mr Christian van de Voorde [personal communication], much
of the information being put about by the general public was wildly inaccurate.
Unfortunately, the situation on the ground remained unstable for more than a week
and, during this time, GFB was not able to gather accurate information with which
to counteract rumours and exaggerations. In this respect, the impact of social media
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on the public image of the incident was decidedly negative because it remained
distorted, inaccurate and alarmist. When a situation is simpler and more easily
interpretable, one may be able to rely on self-policing of social media by users who
are concerned to get the facts right, but when the true facts are, on the instant,
unobtainable or in dispute, that cannot be the case.
A further example is that of the massive surge in social media activity in the
aftermath of Hurricane Sandy, which impacted the Atlantic coast of the United
States at the end of October 2012. There is no doubt that social media did provide
the opportunity for greatly enhanced exchange of information between the
authorities and the public and between members of the public, but not without
substantial costs (CSS-ETH 2013, p. 4). Photoshop-style image manipulation was
widely used by people who shared photographs of the storm. Exaggerated and false
news items, for example, about which places in New York City were flooded, were
shared and reposted by so many social media users that they were picked up by
mainstream media and thus began to assume the status of true stories until they
could be discounted by field checking.
Murthy (2011b, p. 11) noted that the very people who are most in need of support
may be those who have least access to and understanding of the technology that they
would need in order to participate in the social media revolution. But apart from the
basic digital divide between the ‘haves’ and ‘have nots’, researchers have noted the
persistence of demarcations on the basis of race and class among users of the
technology and services.
Perhaps the greatest challenge in using social media is the sheer volume of
information involved. One researcher (Goolsby 2009, p. 3) commented that ‘‘finding
useful ‘tweets’ during a major event… is a little like panning for gold in a raging
river.’’
According to Cheong and Lee (2011), ‘‘Twitter has been identified as both a
potential facilitator and also a powerful deterrent to terrorism.’’ Hence, there is
currently considerable ambiguity about whether social media exert a benign or a
malign influence on public safety and security. For example, although China is
known for its attempts to repress free usage of the Internet, there is an alternative
story. Denis-Remis et al. (2013) described how patriotic Chinese used social media
to orchestrate disruption of the activities of a French hypermarket company in China
because of anger at French Government policies towards Tibet. Once it had started,
the researchers saw the reaction as something that was impossible to stop, an
indication of the strength of positive feedback in the effects of messaging (DenisRemis et al. 2013, p. 53). This underlines the positive feedback inherent in social
media usage in a crisis, a phenomenon that can generate unstoppable, uncontrollable
developments with little regard to whether posterity will consider them positive or
negative.
Finally, when reviewing the potential drawbacks of social media, one should also
note the physical weaknesses. Writing about social media usage during a major
interruption of electricity supply to the southern Californian city of San Diego,
Jennex (2012b) noted that: ‘‘Ultimately the Great Southwest Blackout can be
considered a massive, unplanned, backup battery test.’’ Neither the users nor the
providers of sites and cellular communication to reach them were ready in any way
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for such an exigency. Tellingly, Jennex (2012b, pp. 4–5) concluded that ‘‘while the
functionality of social media is useful, the maturity of social media availability is
not sufficient to warrant including social media as operational crisis response
systems.’’ In other words, the potential is there, but much needs to be done in order
to realise it. This will require preparedness on both the technical and the social
fronts, from both suppliers and users of services.
One interesting question that deserves to be considered is whether the advantages
and disadvantages of social media with respect to disaster mitigation and response
are significantly different to those of traditional media. If one considers the case of
earthquake prediction, there is little indication that television, radio and newspapers
have behaved rationally, responsibly and within the bounds of scientific fact (see,
for example, Dearing and Kazmierczak 1993). Would social media have closed or
increased the gap between reporting and reality? It is too early to tell. However, the
idea of a message that ‘‘goes viral’’ and is thus picked up by millions of users, is
worrying. For example, the 30-min documentary film Kony 2012, about Joseph Rao
Kony, the Ugandan founder of the Lord’s Resistance Army (LRA) was viewed
almost 100 million times on YouTube, through which it reached more than half of
young adult Americans. Most of the people who saw it know no more about Kony
and the LRA than they found out in the film. However, it has been widely criticised
as being significantly inaccurate and misleading (Cavanagh 2012). This could easily
happen in disasters, and, in so doing, potentially widen the audience beyond those
who would have gained information from the traditional media. On the other hand,
the worldwide misinterpretation of the trial of seven officials after the Italian
L’Aquila earthquake of 2009 shows that the conventional media are just as capable
as social media of picking up a misleading story and vigorously propagating it
(Alexander in press b).
In synthesis, besides problems such as waning battery power, the use of social
media brings forth issues of trust and privacy. As Johnson et al. (2011) observed,
trust is asymmetric, personalised, dependent on context and potentially short-lived.
Moreover, privacy is an increasing concern that is shared by many users of social
media.
Ethics of Social Media Usage in Disaster
Students of social media have been quick to take note of potential ethical dilemmas.
The first to investigate this aspect were legal and medical researchers. For example,
the associations that represent medical personnel in the United States have
counselled against uninhibited use of social networking, as it can lead to conflicts of
interest, for example, when a doctor uses social media to befriend a patient. Decamp
(2013) noted that problems such as this are a legal minefield, and one that lawyers
have increasingly come to monitor in search of opportunities to litigate. Emergency
managers normally have to walk a tightrope between actions that may be deemed
excessive and any failure to respond adequately that could be considered negligence
(Alexander in press a). As McKee (2013, p. 3) observed, ‘‘The changing nature of
technology, as well as the relatively recent use of social media for research, means
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that ethical considerations will have to be reviewed regularly.’’ The same will be
true of protection against unwarranted official intrusions into personal privacy
(Nissenbaum 2004).
According to Nissenbaum (2004), privacy is subject to a set of norms about what
can be divulged and how that can happen, but the norms vary from one social
context to another. This is the theory of ‘contextual integrity’. Violation of the
norms amounts to a loss of privacy. Grodzinsky and Tavani (2010) noted that norms
established or respected by one participant, for example the author of a personal
blog, can easily be violated by the republication of material in a different context,
for example, a public blog.
As noted above, risks are associated with a largely unregulated Internet-based
system of public mass communication. In summary, the use of social media for
nefarious or malignant purposes could potentially include attempts to persecute
people or damage their reputations (Boggs and Edwards 2010), attempts to spread
malicious rumour, efforts to foment violent protest, and attempts to organise
terrorist activities. Lesser degrees of harm could involve invasion of privacy and
unauthorised dissemination of personal information. Moreover, any system of
disaster response or risk reduction that depends on social media for access to its
services risks excluding those people who lack access to the requisite means. No
amount of self-congratulation about the high levels of penetration of ‘smart’ mobile
telephony can obscure the fact that there are citizens who for reasons of poverty,
disability or choice do not possess the instruments in question and do not know how
to use them. Moreover, it is clear that the wealthier, younger, fitter and more aware a
person is, the more he or she is likely to be fully aware of the services available via
social media and its potential under different circumstances. ‘‘Computer illiteracy’’
is a form of disadvantage in a world that has become dependent on digital
communication for many services. It is only partially compensated for by the fact
that, by relaying information by word of mouth, other people will be able to help a
disadvantaged individual cope. However, total equality cannot be a sine qua non of
social media, as there will always be some level of social exclusion to hinder their
development.
If these problems become serious, critics will begin to argue that the democratic
function of social media is a mere illusion. Instead, we see the media as a means of
propagating and sustaining direct democracy, and of fostering participatory
governance in disaster risk reduction. In this respect, it should be borne in mind
that there is a difference between disseminating information and giving people
executive power on the basis of what is disseminated. Nevertheless, even the mere
propagation of information is empowering, to a certain extent.
The risk of concerted abuse of social media begs the question of whether they
should be more regulated, and if so, how could that be achieved? Regulation would
require an assessment of the potential seriousness of the problem, estimation of
whether measures to control social media are feasible, and a decision on whether the
measures are necessary and would help abate the problem.
Social media and the Internet constitute a truly open system, and one that has no
centre. As Brafman and Beckstrom (2006) noted in their book The Starfish and the
Spider, when such a system is under attack it tends to mutate into something that is
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even less centralised and even harder to control. Thus, attempts in the People’s
Republic of China and the Islamic Republic of Iran to dictate what people can
access on the Internet are only partially successful: they slow down rather than stop
the dissemination of information. In the main, the question of how one polices a
leaderless organisation is largely unsolvable. Individuals can be tracked down and
arrested, sites can be taken down, services can be blocked or wound up, but others
will replace them.
The converse view is that social media are a good means of circumventing
corruption, mendacity, unwarranted control and excessive monitoring of people’s
activities. Moreover, we can view social media as a source of charity, solidarity and
hope. While we should beware of treating such a system as a nirvana of democracy,
while there is a good consensus among users about what is right and good, and what
is acceptable, self-policing will be active. Bad posts and unethical messages will be
censured by the users. In this respect, we can return to Charles Fritz’s (1961)
conception of disasters as the home of the ‘‘therapeutic community’’—cf. Alan
Barton’s ‘‘altruistic community’’ (Barton 1970) and Taylor’s ‘‘utopian feelings’’
(Taylor et al. 1970). In the immediate aftermath of a sudden-impact disaster, there
tends to be a greater consensus in the community on what is right, good and ethical
to think, say and do. Differences are put aside for the duration of the emergency, as
the community faces a large external threat, for example the destruction caused by
an earthquake, hurricane or flood. This is the period in which social media come
into their own as a source of communication and support. Hence, they can be said to
benefit from and reinforce the ‘‘therapeutic community’’, in a form of social
symbiosis.
One other aspect of the ethics of social media usage deserves to be examined
here. I have written elsewhere (Alexander in press b) of the ‘‘death of discretion’’ in
modern culture. In fact, wireless communication is part of a broad trend towards the
gradual abandonment of personal discretion and increasing tendency to share
intimate details. For example, people grieve in public far more than they did in the
early days of mass media. Social media facilitate mass participation in this process.
Those who go against the grain and pose grossly offensive messages in relation to
people’s grief at losses are likely to be pursued vigorously by the authorities, as the
level of outcry forces action to be taken. Social media can thus produce a very
robust consensus, but not an absolute one.
There is an ethical question about the misrepresentation of disaster, whether this
is deliberate, inadvertent or a combination of the two (Singer and Endreny 1994).
The first ‘‘modern disaster’’ was probably the famine and starvation that occurred in
the Biafran war of secession from Nigeria in 1967–1970. This was the first occasion
on which film footage of death and suffering in an African famine were shared with
the Western public in near real-time. However, the famine was not the result of
natural disaster or inability to produce food, as the television viewers believed, but
was a tactic of war, the result of blockades and military incompetency (Mayer
1969). Decades later, the Live Aid concerts and ensuing donation bonanzas
propagated the misconception that Ethiopians were incapable of responding to
catastrophic drought, when in reality they were the victims of forced migration,
which was practically sustained by the donation spree (Müller 2013). Theoretically,
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social media are able to correct the imbalances of perception, because realistic
reports are likely to arrive from the field. However, much depends on who takes
note of the reports and how they are mediated by social perception. For research,
this is largely uncharted territory.
One is prompted to ask whether there are any solutions to the ethical problems
that at least potentially, and in some cases demonstrably, beset social media usage in
disasters. In more general terms, high-profile cases of electronic media-based
‘‘stalking’’ and persecution, propagation of racism, endangerment of minors, threats
of violence and incitements to criminal activity have prompted the authorities of
various countries to discuss or adopt measures to take the offenders off line, track
them down and, where appropriate, prosecute them. With respect to deliberate
misuse of information in disasters, rarely have there been punitive measures with
regard to the traditional media, let alone social media. However, the trial of the
‘‘L’Aquila seven’’ (Alexander in press b) is a landmark case in which the misuse of
information given to the public was at the heart of the legal case. In that the
prosecution successfully demonstrated that the results of this were fatal for some
tens of recipients, the way has been opened for legal action on information that is
harmful through negligence or design.
Some Recent Successes in the Use of Social Media in Disasters
Despite the potential for negative uses of social media, there have already been some
success stories in their employment for disaster response and risk reduction. Social
networks have been used instantly and spontaneously to report health issues, such as
cholera in Haiti and dengue in Thailand and Indonesia (Resch et al. 2011). In Japan
after the March 2011 earthquake and tsunami, social media facilitated public alerts,
helped locate missing people and enabled mapping of different aspects of the
emergency (Hjorth and Kim 2011). Flash-flooding in January 2011 in Queensland
and Victoria, Australia, led to a six-fold increase in public accession to emergency
service Facebook sites, representing a huge increase in interest and support (Bird
et al. 2012). Researchers have developed an on-line monitoring tool to detect sharp
increases (‘bursts’) in the frequency of key words that appear on Twitter (Cheong and
Lee 2010). Furthermore, rumours and misuses of Twitter are being monitored by
researchers at the University of Indiana, via a website called Truthy (truthy.indiana.edu). Lastly, the proliferation of crisis camps and their aggregations, crisis
commons, has started to promote the more systematic organisation of social media
for emergency response, on occasion using wikis (Blanchard et al. 2010).
Conclusion
The current situation regarding social media in disasters and risk reduction has been
summarised very well by Sutton et al. (2008, p. 7):
Our data suggest that social media support the influence of the existing publicside information production and distribution. As a consequence of the growing
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utility of social media and the ubiquity of peer-to-peer communications, we
believe that a change in disaster management models will come about in spite
of any failure to formally recognize these widely distributed and often
strikingly well-organized information activities. However, we argue that
simply letting these inevitable changes take place would nevertheless result in
needless delay, conflict and missteps. Instead, we call for efforts by public
officials to actively consider how to align with peer-to-peer information
exchange and to develop new conceptualizations of the information production and dissemination functions for disaster response.
In other words, the incorporation of social media into pre-existing emergency
management systems is inevitable, owing to the sheer weight of public usage of
such facilities. Moreover, as social networks can be two-way means of communication, they can mix popular and official information. In this optimistic view, the
citizenry is viewed as a powerful, self-organising and collectively intelligent force
(Gao et al. 2011b).
Lastly, it is notable that, after only a very few years of research, there are still
many aspects of social media usage in crisis that are not adequately understood. One
of these is the influence of gender on perception, attitudes and behaviour regarding
usage of the new media (Armstrong and McAdams 2009). If social media are to be
optimised as a means of communication during emergencies, such aspects will have
to be understood thoroughly.
In synthesis, social media offer immense potential for interaction with the public
and monitoring of the public’s concerns. They have greatly increased the scope,
volume and speed of information exchange. This has not occurred without risks,
mostly associated with the propagation of false or inaccurate information, and the
potential consequences if this takes place. However, mass participation tends to
rectify some of the inadequacies associated with the free and unregulated flow of
information. The future will probably see a rationalisation of the use of social media
and new methodologies for judging the public mood and the utility of information
supplied by the public. This will be a challenge that emergency planners and
managers must necessarily face.
One final point concerns the role of social media in the long periods dominated
either by protracted recovery from major disasters or by mitigation (disaster risk
reduction). Patient attempts will need to be made to incorporate social media into
these processes and during them the technological, cultural and social realities will
inevitably change. There is a strong need for institutions such as civil protection
services and emergency warning systems to be adapt to the changing reality of
social media, and also to ensure that they have robust plans to tackle any ethical
dilemmas that social media usage may produce in the future.
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Psychology of Violence
2017, Vol. 7, No. 2, 316 –327
© 2016 American Psychological Association
2152-0828/17/$12.00 http://dx.doi.org/10.1037/vio0000056
Psychological Outcomes in Reaction to Media Exposure to Disasters and
Large-Scale Violence: A Meta-Analysis
Tanya L. Hopwood and Nicola S. Schutte
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
University of New England
Objective: A quantitative meta-analysis set out to consolidate the effect of experimental studies of media
exposure to disasters and large-scale violence on negative psychological outcomes. Method: The
meta-analysis included 18 experimental studies with an overall sample size of 1,634 to obtain an overall
effect size and information regarding moderators of the effect size. Results: An overall significant and
large effect size of Hedges’ g of 1.61 showed that, across studies, media exposure to disasters and
large-scale violence was followed by negative psychological outcomes. Outcome type was a significant
moderator, with anxiety reactions showing an especially strong effect. Community sensitization was a
significant moderator, with studies conducted in a region that had recently been exposed to the type of
disaster or violence portrayed in the media showing especially large effect sizes. Conclusion: The results
indicate that media exposure to disasters and large-scale violence can cause negative psychological
outcomes, at least transiently. Limitations included a lack of statistical power in some moderator analyses
and the inability to draw inferences about the duration of effects. There is a need for further research
aimed at identifying the possible cumulative effects of media exposure and identification of groups at
greatest risk for harmful outcomes.
Keywords: media exposure, disaster, violence, meta-analysis
antecedent of posttraumatic symptoms (Houston, 2009; Pfefferbaum et al., 2014), and Murray (2008) claimed that the extant
research has supported three types of effects of televised violence—increased aggression, desensitization, and fear. Further,
Wilson (2008) concluded that children’s extensive use of screen
media (including violent material) may affect their socialization,
though these effects may be mediated by factors such as age,
gender, the extent to which they identify with the characters
depicted, and how real they believe the media content to be.
Although some studies have found either no effect or beneficial
effects of disaster-related media exposure (Linley, Joseph, Cooper,
Harris, & Meyer, 2003; Williams & Khan, 2011), and other
researchers have asserted that media exposure may only exacerbate preexisting symptoms of trauma (Ahern et al., 2002), the
majority of studies suggest that media consumption of disaster and
large-scale violence-related material may evoke psychological reactions similar to those experienced by direct victims of trauma
(Houston, 2009; Pfefferbaum et al., 2014; Slone & Shoshani,
2010). Longitudinal and survey studies found that people distally
located from the September 11 terrorist attacks of 2001 and exposed to the events primarily via mass media experienced significant personal threat and posttraumatic stress reactions (Callahan,
Hilsenroth, Yonai, & Waehler, 2005; Dougall, Hayward, & Baum,
2005; Schuster et al., 2001; Silver, Holman, McIntosh, Poulin, &
Gil-Rivas, 2002). Some studies found a positive association between hours of September 11 TV coverage consumed and stress
reactions (Blanchard et al., 2004; Schlenger et al., 2002), and other
researchers identified a link between disaster-focused distress and
perceived similarity to the victims as depicted by media (Wayment, 2004).
Although substantial research has been conducted in the area of
media exposure to disasters and large-scale violence, most of this
Advances in technology are affording people unprecedented
second-hand exposure to disasters and large-scale violence (Kaplan, 2008; Slone & Shoshani, 2010). Given the vast number of
people consuming modern media and the growing propensity
of news outlets to employ techniques such as rolling coverage of
disasters and large-scale violence as they occur (Jain, 2010; Kaplan, 2008), it is increasingly important for research to explore the
potential impact of threat-related content. The purpose of the
present study was to consolidate the effect of experimental studies
of media exposure to disasters and large-scale violence on negative
psychological outcomes.
There has been a long-standing academic debate as to whether
or not media with violent content can constitute exposure to
violence. Some scholars claim that much of the research linking
violent media to aggressive behaviors has drawn unfounded inferences of causation from largely correlational research (Grimes &
Bergen, 2008). In addition, the Diagnostic and Statistical Manual
of Mental Disorders (5th ed.; DSM–5; American Psychiatric Association, 2013) has amended the previous version (4th ed., text.
rev.; DSM–IV–TR; American Psychiatric Association, 2000) to
explicitly state that media consumption cannot constitute exposure
to trauma for a diagnosis of posttraumatic stress disorder (PTSD).
Bolstering the other side of the debate, numerous studies have
found evidence to suggest that media exposure may act as an
This article was published Online First May 5, 2016.
Tanya L. Hopwood and Nicola S. Schutte, School of Behavioural,
Cognitive, and Social Sciences, University of New England.
Correspondence concerning this article should be addressed to Nicola S.
Schutte, Psychology, University of New England, Psychology Lane, Armidale, Australia. E-mail: nschutte@une.edu.au
316
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
MEDIA EXPOSURE TO LARGE-SCALE VIOLENCE
research has employed self-report survey methods. These studies
provide valuable details and are rich in ecological validity, collecting information on how individuals have chosen to consume
media and retrospectively recording subjective reactions. Researchers have examined media forms such as TV, newspaper,
radio, and the Internet, and have looked at coverage of both
terrorist events and natural disasters. Many such studies have
found strong links between disaster-related media consumption
and negative psychological outcomes, including increased anxiety
(Schuster et al., 2001), fear and depression (Lachlan, Spence, &
Seeger, 2009), a heightened sense of threat (Maeseele, Verleye,
Stevens, & Speckhard, 2008), aggression (Argyrides & Downey,
2004), and posttraumatic stress symptomology (Pfefferbaum, Pfefferbaum, North, & Neas, 2002; Pfefferbaum et al., 2000; Schlenger
et al., 2002).
A recent descriptive research synthesis by Pfefferbaum et al.
(2014), which examined correlational studies of the relationship
between disaster-related media consumption and psychological
outcomes, found evidence of an association between TV viewing
of disaster news and negative outcomes such as posttraumatic
stress (PTS) symptoms, stress reactions, depression, and fear.
Similarly, a meta-analysis by Houston (2009) found a significant
overall effect size (r ⫽ .162) for the relationship between
terrorism-related media consumption and PTS. However, as with
the individual studies, the correlational nature of the data comprising these meta-analyses does not allow for inferences regarding
causality; people who watch traumatic events on the news may
consequently experience fear. Alternatively, people experiencing
fear may watch traumatic news, perhaps for information-seeking,
surveillance purposes, or reassurance.
Longitudinal studies that measured psychological dimensions
pre- and postdisasters (Cohen et al., 2006; Kennedy, Charlesworth,
& Chen, 2004; Otto et al., 2007; van Zelst, de Beurs, & Smit,
2003) have helped support the theory of media exposure to disasters and large-scale violence effecting negative psychological outcomes. These studies, although again high in ecological validity,
cannot control for a range of potentially confounding exposure
variables, and so are unable to isolate the effects of media.
Although many researchers have used experimental methods to
explore individual psychological reactions to media exposure to
disasters and large-scale threats, no meta-analysis of these studies
exists. By conducting a meta-analysis of experimental studies of
media exposure to disasters or large-scale violence, we aimed to
identify an overall effect size for psychological outcomes and also
consolidate information regarding the main types of reactions to
such media exposure. A review of the literature indicated that
anxiety (or stress) and anger are commonly measured outcomes
(Lerner, Gonzalez, Small, & Fischhoff, 2003; Pfefferbaum et al.,
2014). As pointed out by Slone and Shoshani (2010), the experience of these emotions is predicted by the theory of protection
motivation (Rogers, 1983). This theory asserts that when a person
interprets a situation as threatening, anxiety will often result. This
anxiety may promote a need to defend the self and others, which
may in turn lead to anger. We believe that this theory may help
provide a useful scaffold for understanding how media exposure to
disasters and large-scale violence may communicate a sense of
personal or community threat, which may in turn provoke reactions such as anxiety, anger, and other forms of negative affect.
317
Another theory that may add to the conceptual framework for
understanding people’s reactions to this type of media content is
the conservation of resources theory (Hobfoll & Lilly, 1993). The
conservation of resources theory claims that a person’s ability to
cope with challenges depends on his or her perceived inventory of
practical, social, and emotional resources. Maguen, Papa, and Litz
(2008) posited that large-scale threats (such as terrorism) intensify
perceptions of resource loss in areas such as self-esteem, selfefficacy, and internal locus of control. The loss of these safeguarding resources may increase levels of negative affect and
diminish adaptive coping (Moos & Holahan, 2003). Brewin, Andrews, and Valentine (2000) showed that many studies have supported a cascading effect of perceived resource loss, with multiple
stressors leading to increased vulnerability to further stress. If it
can be demonstrated that one-time media exposure to disasters or
large-scale violence plays a causal role in negative psychological
outcomes— even transiently—this may suggest the presence of
maladaptive and more enduring effects in some individuals as the
result of cumulative long-term exposure.
In the current meta-analysis, we predicted that across studies,
there would be a significant effect size for the impact of media
exposure to disasters or large-scale violence on negative psychological outcomes. There are a number of variables that we believed
might moderate outcomes across studies: intentionality of the
event portrayed, media format, whether the study was conducted
before or after September 11, community sensitization to trauma in
relation to the sample, and differences in participant sample gender
and age. The background for selection of these moderator variables
follows.
Intentionality of Event
Research has indicated that a disaster designed with human
intent (e.g., a terrorist attack) may be associated with a higher risk
of subsequent psychopathology than a disaster of accidental or
natural origin (DiMaggio & Galea, 2006). In addition, research
results have suggested that different forms of emotions may be
more common in the wake of accidental versus intentional trauma
(e.g., anger for intentional events, fear for random events; Rosoff,
John, & Prager, 2012). We examined whether portrayals of intentionally created disasters would result in stronger negative psychological outcomes.
Media Format
Communications research has provided evidence for the efficacy of video footage, compared with more traditional forms of
media such as newsprint or radio, in creating a more emotionally
arousing experience—a sense of realism that has been referred to
as presence (Lombard & Ditton, 1997). Graphic footage of disasters may evoke a sense of immediacy and engagement, and perhaps even a potent communication of threat (Callahan et al., 2005;
Cho et al., 2003). Meta-analytic studies and research syntheses of
correlational research (Houston, 2009; Pfefferbaum et al., 2014)
indicated that consumption of disaster or large-scale threat news
via TV is significantly associated with numerous negative psychological outcomes, including PTSD, PTS, depression, anxiety, and
anger. We examined whether video portrayal of disasters would be
associated with larger effect sizes.
HOPWOOD AND SCHUTTE
318
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The Impact of September 11
Much research on media consumption of disasters and largescale violence occurred in the wake of the terrorist attacks in the
United States on September 11, 2001 (Neria & Sullivan, 2011).
The rolling coverage of these events in the media continued for
days, and then sporadically during the weeks and months that
followed, giving millions of people across the globe access to
details of the disaster (Pfefferbaum et al., 2002). The extensive
coverage and large scale of the mass casualties that occurred may
have evoked changes in belief systems related to safety and security for many individuals (Linley et al., 2003). We examined
whether post-September 11 studies would show stronger effect
sizes.
Community Sensitization to Trauma
Although some theorists contend that previous exposure to
trauma may serve as a form of inoculation against adversity
(Eysenck, 1983, as cited in Shrira, Palgi, Hamama-Raz, Goodwin,
& Ben-Ezra, 2014), many studies have indicated that a history of
previous trauma increases susceptibility to adverse psychological
outcomes, such as PTSD (Brewin et al., 2000; Chatard et al., 2012;
Shrira et al., 2014). Some global locations have had more recent
direct experience of disasters (e.g., war, terrorism, disease, and
natural disasters) than others. In the current meta-analysis, the
global region in which each experiment was conducted was coded
as a possible moderator variable. Also, an additional variable
called community sensitization was created to identify whether or
not the region in question had recently (within the previous 5
years) experienced a disaster of the type portrayed in the stimulus
material. We examined whether studies conducted in areas that
have recently experienced large-scale disaster or violence would
show larger effect sizes.
contended that children may be a particularly vulnerable population in terms of adverse PTS reactions (Comer & Kendall, 2007;
Dirkzwager, Kerssens, & Yzermans, 2006; Pfefferbaum, 1997;
Saylor, Cowart, Lipovsky, Jackson, & Finch, 2003). We examined
whether studies of adults with older participants would show
stronger effect sizes and whether studies with child participants
would show stronger effect sizes.
Current Study
The current study aimed to consolidate findings of experimental
research providing information regarding the causal impact of
disaster-related media exposure on psychological reactions through a
meta-analysis. Our predictions are as follows.
Hypothesis 1: Across studies, there is a significant effect size
for the impact of media exposure to disasters or large-scale
violence on negative psychological outcomes.
Hypothesis 2: Media portrayals involving intentionality result
in stronger negative psychological outcomes.
Hypothesis 3: Video portrayal results in larger effect sizes.
Hypothesis 4: Post-September 11 studies show larger effect
sizes.
Hypothesis 5: Studies conducted in areas recently experiencing large-scale disaster or violence show larger effect sizes.
Hypothesis 6: Studies with a higher percentage of females
show larger effect sizes.
Hypothesis 7: Studies with older participants or child participants show stronger effect sizes.
Method
Individual Differences
In the correlational research of media consumption of disasters
and large-scale violence and psychological outcomes, the most
widely replicated moderating variable is gender, with females
consistently demonstrating greater susceptibility to negative outcomes than males (Baum, Rahav, & Sharon, 2014). It has been
suggested that this gender effect may be partially accounted for by
women’s higher levels of fear for others (altruistic fear; Nellis &
Savage, 2012), heightened empathy (Nellis, 2009), increased levels of perceived vulnerability (Baum et al., 2014; Nellis, 2009), or
greater propensity to acknowledge distress (Lachlan, Spence, &
Nelson, 2010). We examined whether studies with a higher percentage of females would show stronger effect sizes.
Eysenck’s (1983) inoculation theory (as cited in Shrira et al.,
2014) suggests that older people have experienced more challenges across their lifetimes and have thus developed greater
resilience—a quality that may help protect them from the adverse
effects of further trauma. Some correlational studies have found
evidence to support these inoculation and maturation effects (e.g.,
Schlenger et al., 2002; Shrira et al., 2014). However, other studies
have found that elderly people may be more susceptible than
younger people to PTSD and other detrimental outcomes (e.g.,
Kun, Han, Chen, & Yao, 2009). Further, many researchers have
Inclusion and Exclusion Criteria
Studies were deemed eligible if they used an experimental
methodology in a controlled environment to measure individuals’
psychological outcomes in response to media coverage of disasters
or large-scale violence. The key terms were operationalized as
follows: media coverage (the independent variable [IV]) included
factual reports from TV, Internet, radio, newspaper articles, or
realistic simulations of any of these. Disasters or large-scale violence included major accidents (e.g., plane crashes or multiple road
accidents), natural disasters (e.g., hurricanes), acts of terrorism,
war or combat, climate change, economic crises, and crime with
the potential for casualties. Psychological outcomes (the dependent
variable [DV]) included state anxiety, negative affect, fear, or
perceived threat from the type of trauma in the exposure condition.
The DV could also include other negative outcomes— either emotional or cognitive—such as anger or blame, or positive outcomes
such as trust and empathy. One might expect outcomes such as
trust to decrease after some media exposure, such as coverage of
a terrorist attack, and other outcomes, such as empathy, to increase
after other media exposure, such as coverage of a natural disaster.
Eligible studies needed to either assign groups across the IV
(e.g., media exposure to disaster or large-scale threat content vs.
MEDIA EXPOSURE TO LARGE-SCALE VIOLENCE
neutral content) or use repeated measures, with pre- and postexposure measures on the DV. Given the meta-analysis aimed to
assess effect size variability across ages, genders, and locations,
eligible populations included the general public in any geographical region.
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Search Strategies and Data Extraction
In June and July 2015, the PsycARTICLES, ProQuest, and
Summon bibliographic databases were used to carry out a systematic search for experimental studies measuring psychological outcomes in the context of media exposure to disasters and large-scale
violence. Keywords included “media coverage,” “media exposure,”
“television news,” “disaster media coverage,” “newspaper,” “internet
news,” “terrorism,” “war,” “natural disaster,” “virus,” “pandemic,”
“crime,” “anxiety,” “negative affect,” “fear,” “threat,” “anger,” “positive affect,” and “experiment.” A series of search expressions were
created for each disaster type to cover all relevant possibilities (for
example, terrorism AND [“media coverage” OR “television
news”] AND [anxiety OR “negative affect” OR fear OR threat OR
anger OR “positive affect”] AND experiment).
To ensure that the search was methodical and met recommended
guidelines for meta-analysis research, the PRISMA search protocol (Moher, Liberati, Tetzlaff, Altman, & PRISMA Group, 2009)
was used to record all articles identified, screened, and assessed for
eligibility. The reference list of each eligible article was reviewed
and assessed for additional relevant studies, and Google Scholar
was used to search for relevant research by identified experts in the
field. Separate eligible reports by the same research teams were
examined to ensure the use of independent data sets.
Finally, each study was assessed to determine whether adequate
information was provided to ensure suitability of the stimulus
material (exposure group media content), and whether the methodology was appropriate for the purpose of determining a causal
relationship between the IV and DV. Studies were excluded if
there were insufficient data to allow for the calculation of an effect
size of at least one relevant DV.
In total, 4,364 reports were identified through the database
searches, with an additional 137 reports obtained through other
sources, such as a search of literature cited in pertinent articles.
After removal of duplicate items, 2,565 records remained. Screening via title and abstract (and full text when necessary) resulted in
the exclusion of 2,523 reports that either did not employ an
experimental methodology, did not manipulate an appropriate
form of media exposure, or did not measure a relevant outcome. Of
the remaining 42 eligible reports, three were excluded because of
insufficient information regarding the stimulus media material, 20
were excluded because of methodologies that were incompatible
with the research question (e.g., correlational studies), and four
were excluded because of insufficient reported data to allow for
calculation of an effect size of at least one relevant DV. Ultimately, the search resulted in 15 reports containing 18 studies
suitable for inclusion in the meta-analysis (see Table 1). Some
groups that were not appropriate for testing our hypotheses (such
as those using a treatment condition prior to media exposure) were
excluded; the experimental groups excluded from each study and
the rationales for these decisions are outlined in Table 2. The
overall sample size was 1,634, with 959 females (58.7%) and 675
males (41.3%).
319
Publication Status of Studies
Several eligible unpublished reports were located during the
search phase but were excluded because of incompatible methodologies or insufficient information. Thus, all studies included in
the meta-analysis were published.
Coding Procedures
Following the recommendations of Cooper (2010), all studies
were coded separately by two raters. The coding was consistent
across raters (97% agreement) and disparities were resolved
through discussion.
Outcome types. The studies included in the meta-analysis
measured a variety of psychological outcomes, most considered
negative (e.g., state anxiety, anger, perceived threat), but some
with positive valence (e.g., trust and empathy). To allow us to
investigate whether type of outcome impacted effect size, each
outcome in each study was coded in one of six broad categories—
state anxiety, negative affect, fear, perceived threat, other negative
outcome (e.g., anger), and positive outcome.
Moderator variables. Based on the findings of correlational
research and the theories espoused by previous researchers (as
mentioned in the introduction), several study variables were coded
with the aim of assessing their influence on the effect size of
psychological outcomes. Moderator variables included intentionality (intentional, unintentional, mixture); media format (video,
audio, print, static images, mixed), date of study (pre- or postSeptember 11, 2001), global location (U.S., Middle East, Europe/
GB, Asia, Australia, other), community sensitization to disaster
type (exposure or no exposure to given disaster type within the
previous 5 years), gender breakdown (percentage of females), and
mean age of participants.
Study quality. Given the potentiality for study quality to
impact results, study design and the reliability of psychometric
measures (for DVs) were coded as moderator variables. Study
design was coded with four levels of empirical design: (a) pre–post
measures with no control group; (b) experimental and control
groups with no random assignment; (c) random assignment to
experimental and control group—posttest only; and (d) random
assignment to experimental and control group—pre- and postmeasures. The reliability of psychometric measures for the outcomes
(DVs) was coded as a continuous variable, with a mean Cronbach’s alpha calculated for outcomes in each study (five of the 18
studies had missing data for this variable).
Data Analysis
All data analyses were performed using Comprehensive MetaAnalysis Version 3 (CMA; Biostat, Inc., 2013). As most studies
reported results in the form of means (and standard deviations) for
exposure and control groups, and based on the recommendation of
Borenstein, Hedges, Higgins, and Rothstein (2009), Hedges’ g was
chosen for the effect size metric. The meta-analysis provided a
weighted mean summary effect size for negative psychological
outcomes. Positive outcomes (e.g., trust and empathy) were included but were entered to reflect an opposite-effect direction
when appropriate. For the main analysis, if outcomes of different
types were reported for the same group of participants in a study,
101
58
58
120
120
60
67
67
80
22
40
40
40
40
40
40
116
248
100
100
100
237
43
43
84
84
100
100
40
78
78
78
Barlett and Anderson (2014, Study 2)
Boyle (1984)
Boyle (1984)
Comer et al. (2008)
Comer et al. (2008)
Fischer et al. (2007, Study 2)
Fischer et al. (2007, Study 4)
Fischer et al. (2007, Study 4)
Fischer et al. (2010, Study 1)
Fischer et al. (2010, Study 3)
Fischer et al. (2011, Study 1)
Fischer et al. (2011, Study 1)
Fischer et al. (2011, Study 1)
Fischer et al. (2011, Study 2)
Fischer et al. (2011, Study 2)
Fischer et al. (2011, Study 2)
Lightstone et al. (2005–2006)
Ortiz et al. (2011)
Shoshani and Slone (2008)
Shoshani and Slone (2008)
Shoshani and Slone (2008)
Slone (2000)
Slone and Shoshani (2006)
Slone and Shoshani (2006)
Slone and Shoshani (2008)
Slone and Shoshani (2008)
Slone and Shoshani (2010)
Slone and Shoshani (2010)
Williams and Khan (2011)
Zeidner et al. (2011)
Zeidner et al. (2011)
Zeidner et al. (2011)
19.24
22.60
22.60
10.80g
10.80g
30.37
24.68
24.68
27.43
41.47
25.67
25.67
25.67
26.85
26.85
26.85
NR
9.24
22.65
22.65
22.65
34.70
22.65
22.65
22.65
22.65
23.00
23.00
NR
24.44
24.44
24.44
Mean age
73
83
83
61h
61h
52
81
81
63
73
50
50
50
50
50
50
78
54
50
50
50
50
50
50
50
50
50
50
50
59
59
59
%Femalea
Other (Econ.)
Acc./Nat.
Acc./Nat.
Terrorism
Terrorism
Terrorism
Mixture
Mixture
Terrorism
Terrorism
Terrorism
Terrorism
Terrorism
Terrorism
Terrorism
Terrorism
Terrorism
Acc./Nat.
Terrorism
Terrorism
Terrorism
Terrorism
Terrorism
Terrorism
Terrorism
Terrorism
Terrorism
Terrorism
Terrorism
Terrorism
Terrorism
Terrorism
Disaster type
U
U
U
I
I
I
M
M
I
I
I
I
I
I
I
I
I
U
I
I
I
I
I
I
I
I
I
I
I
I
I
I
Intent.b
Video
Video
Video
Video
Video
Print
Images
Images
Mixed
Images
Images
Images
Images
Print
Print
Print
Print
Video
Video
Video
Video
Video
Video
Video
Video
Video
Video
Video
Video
Video
Video
Video
Media
3
1
1
1
1
3
3
3
3
3
3
3
3
3
3
3
4
3
4
4
4
4
4
4
4
4
4
4
3
3
3
3
Study designc
U.S.
AUS
AUS
U.S.
U.S.
EUR/GB
EUR/GB
EUR/GB
EUR/GB
EUR/GB
EUR/GB
EUR/GB
EUR/GB
EUR/GB
EUR/GB
EUR/GB
U.S.
U.S.
ME
ME
ME
ME
ME
ME
ME
ME
ME
ME
U.S.
ME
ME
ME
Location
No
Yes
Yes
No
No
No
No
No
No
Yes
No
No
No
No
No
No
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
Sensitizationd
Neg.
SA
Neg.
SA
PT
PT
Neg.
Pos.
PT
PT
NA
PT
Pos.
NA
PT
Pos.
SA
SA
SA
Neg.
Pos.
SA
SA
Neg.
SA
Neg.
SA
Neg.
SA
NA
PT
Pos.
Outcome
.91
NR
NR
.88
.84
NR
.86
.87
.84
NR
.86
.79
.88
.86
NR
NR
.89
.85
.95
.94
.83
.94
.92
.91
.95
.94
.95
.94
.89
.90
.90
.94
Reliability (␣)e
1.028
.759
.532
.832
.341
.520
.401
.683i
.561
1.950
1.021
.598
.183i
.780
.456
.466i
.857
.427
11.034
8.241
6.182i
1.662
5.122
4.925
6.588
.617
10.823
7.009
⫺1.429
.768
.768
.447i
ESf
1.028
.607
.607
.504
.504
.520
.542
.542
.561
1.950
.496
.496
.496
.542
.542
.542
.857
.427
7.910
7.910
7.910
1.662
5.023
5.023
3.603
3.603
8.916
8.916
⫺1.429
.661
.661
.661
Mean ES
Note. NR ⫽ not reported; U.S. ⫽ United States of America; AUS ⫽ Australia; EUR/GB ⫽ Europe or Great Britain; ME ⫽ Middle East; Acc./Nat. ⫽ large-scale accident or natural disaster; Econ. ⫽
economic crisis; SA ⫽ state anxiety; NA ⫽ negative affect; PT ⫽ perceived threat; Neg. ⫽ other negative psychological outcomes; Pos. ⫽ positive psychological outcomes.
a
The percentage of females in the sample to the nearest whole percent. Studies reporting a fairly even gender breakdown were coded as 50%. b Intent. ⫽ intentionality; I ⫽ human agency intentional
event; U ⫽ unintentional event; M ⫽ mixture of intentional and unintentional events. c 1 ⫽ pre–post with no comparison group; 2 ⫽ experimental and control groups with no random assignment;
3 ⫽ random assignment experimental and control group—posttest only; 4 ⫽ random assignment experimental and control group—pre and post. d Sensitization indicates whether the location had a
history of the disaster type portrayed in the media within 5 years prior to study publication. e Cronbach’s alpha values for reported reliability were averaged when more than one measure for that
outcome type was recorded for the study. f Raw effect size for the outcome type, assuming independence of the data for each outcome. Raw effect sizes are shown averaged when more than one
measure for the outcome type (e.g., for type other negative effect) was recorded for the study. g The mean age for child participants in the study (n ⫽ 90); a subgroup of mothers was also included
(n ⫽ 30), but no age data were reported. h The percentage of females across both child and adult participants in the study (48% for child sample; 100% for adult sample). i For positive outcomes,
a high score indicates a less positive outcome.
n
Authors (year, study no.)
Table 1
Characteristics of Included Studies and Effect Sizes
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HOPWOOD AND SCHUTTE
MEDIA EXPOSURE TO LARGE-SCALE VIOLENCE
321
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Table 2
Sample Numbers Used and Excluded From Each Study and Exclusion Reason
Authors (year, study no.)
n used
n excluded
Barlett and Anderson (2014, Study 2)
Boyle (1984)
Comer et al. (2008)
Fischer et al. (2007, Study 2)
Fischer et al. (2007, Study 4)
101
58
120 (90 children,
30 mothers)
60
45
Fischer et al. (2010, Study 1)
Fischer et al. (2010, Study 3)
Fischer et al. (2011, Study 1)
80
22 parents
40
Fischer et al. (2011, Study 2)
Lightstone et al. (2005)
Ortiz et al. (2011)
Shoshani and Slone (2008)
40
116
248
100
20
0
0
200
Slone (2000)
Slone and Shoshani (2006)
237
43
0
77
Slone and Shoshani (2008)
84
84
Slone and Shoshani (2010)
100
200
Williams and Khan (2011)
Zeidner et al. (2011)
40
78
0
0
Exclusion reason
0
0
60 mothers
Excluded mothers who were given experimental
training premedia exposure.
0
22 for each comparison
test
0
22 children
20
the outcomes were averaged. Raw effect sizes (assuming independence of outcomes) for each coded outcome type were also calculated and are reported in Table 1). Subgroup analyses (for the
categorical moderator variables) and metaregressions (for the continuous variables) were based on averaged outcomes for those
studies with multiple outcomes.
A subgroup moderator analysis was conducted to find weighted
effect sizes for each type of psychological outcome represented
(e.g., state anxiety, negative affect, positive outcomes). In order to
make full use of available information regarding different types of
outcomes, in this analysis, each outcome from studies reporting
information for multiple outcomes was used.
According to Borenstein et al. (2009), a random effects model is
the appropriate computational model for most meta-analyses in the
social sciences, in which it usually cannot be assumed that the
primary studies will yield the same effect size. In contrast, a fixed
effects model is appropriate when it can be assumed that all studies
are measuring the same effect in the same population. In the case
of the current meta-analysis, given the variations in study design,
participant groups, locations, and outcomes measured, the effect
sizes were expected to vary and a random effects model was used.
Both experimental groups compared individually
against control (neutral media) group.
Children did not view media.
Meaning group excluded, as this could be
interpreted as an amelioration intervention that
would affect outcome.
As above.
Excluded participants in experimental amelioration
groups (intervention prior to media exposure).
Excluded participants in experimental amelioration
groups (intervention prior to media exposure).
Excluded participants in experimental amelioration
groups (intervention was post media exposure
but Time 2 outcomes recorded after
intervention).
Excluded participants in both pre- and
postexperimental amelioration groups.
indicates that approximately 96% of the variance across studies is
the result of difference in the true effect sizes, rather than sampling
error. The high heterogeneity found here also supports the decision
to explore potential moderator variables.
Results
Overall Mean Effect Size
In order to test the major hypothesis that media exposure to
disasters or large-scale violence results in negative psychological
outcomes, a mean effect size was calculated for all studies included in the meta-analysis (k ⫽ 18). All effect sizes are presented
as standard mean differences in the metric of Hedges’ g (see Table
1). All except one study (Williams & Khan, 2011, with
g ⫽ ⫺1.43) showed a mean effect size indicating an increase in
strength in negative psychological outcomes. The overall mean
weighted effect size for negative psychological outcomes was
large, g ⫽ 1.61 (standard error [SE] ⫽ 0.27, 95% confidence
interval [CI] [1.07, 2.14], p ⬍ .001), indicating that across studies
media exposure to disasters or large-scale violence had a significant effect on negative psychological outcomes.
Heterogeneity Analyses
Inspection of heterogeneity statistics revealed a significant Q
statistic (Q ⫽ 378.53, p ⬍ .001) and a high I2 index (p ⬍ .001,
I2 ⬎ 75%). These results indicate high heterogeneity, with the
effect sizes across studies varying significantly (Cochran, 1954;
Higgins & Thompson, 2002). This variation supports the decision
to use a random effects model, as the I2 index (I2 ⫽ 95.51%)
Moderator Analyses
Method of moments metaregression examined the association
between percentage of females in samples, reliability of measures,
and mean age of samples with effect size. The percentage of females
was significantly associated with the effect size (slope ⫽ ⫺0.059,
SE ⫽ 0.025, 95% CI [⫺0.108, ⫺0.009], Z ⫽ ⫺2.31, p ⬍ .05). These
HOPWOOD AND SCHUTTE
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322
results indicate that the higher the percentage of female participants, the weaker the impact of media exposure on negative
psychological outcomes. However, the regression slope indicated
only a very small association. The metaregression for reliability of
measures also found a significant association (slope ⫽ ⫺0.059,
SE ⫽ 0.025, 95% CI [⫺0.108, ⫺0.009], Z ⫽ ⫺2.31, p ⬍ .05).
These results indicate that the higher the mean reliability level of
measures in each study, the stronger the effect of media exposure
on negative psychological outcomes.
Using a linear metaregression, the mean age of samples was not
significantly associated with the effect size (Z ⫽ 0.30, p ⫽ .76),
indicating that a change in mean age of participants did not
correspond with a linear change in psychological outcomes. Because we predicted a nonlinear relationship (with effects for both
children and older people predicted to be greater than young or
middle aged people), a curvilinear metaregression using a quadratic model was used to test this hypothesis. The curvilinear
model, although not significant (Z ⫽ ⫺1.60, p ⫽ .11), approached
a better fit for the data than did the linear model.
Results of the categorical moderator analyses are shown in
Table 3. Intentionality of the event portrayed did not moderate the
effect size, Q(1) ⫽ 2.73, p ⫽ .098. The effect size difference
between the pre- and post-September 11 groups also was not
significant Q(1) ⫽ 0.52, p ⫽ .47. However, this test lacked power,
with only two studies being conducted prior to September 11,
2001.
Grouping by media format did not yield a significant difference
across effect sizes, Q(3) ⫽ 5.99, p ⫽ .112. As one subcategory of
this variable was a mixture of the other formats, a repeat analysis
excluded the study that used a mixed media format and yielded a
result trending toward significance, Q(2) ⫽ 5.15, p ⫽ .076. Given
that some subgroups were underrepresented (no studies used audio, three used print, and three used images), these results should
be interpreted with caution.
Global location significantly moderated the effect size, Q(3) ⫽
36.17, p ⬍ .001, as did sensitization to disaster type, Q(1) ⫽ 18.54,
p ⬍ .001. The results showed that studies conducted in the Middle
East showed the highest effect sizes. The results also indicated that
studies conducted in communities with a recent history (within the
previous 5 years) of the type of disaster portrayed showed larger
effect sizes than did studies conducted in communities without this
type of threat salience.
Given that the studies in the meta-analysis measured different
types of psychological outcomes, we examined whether the type of
outcome moderated the effect size. As the mean effect across
outcomes for studies with multiple outcomes could not be used
here, we ran this analysis with the assumption of independence of
outcomes within each study (see Table 4). This assumption of a
zero correlation between outcomes represents a conservative approach—it inflates the p value, lowering the statistical power to
detect heterogeneity (Borenstein et al., 2009). The result of this
moderator analysis was significant, Q(4) ⫽ 24.65, p ⬍ .001,
indicating that the strength of the effect varied across the types of
outcomes measured. State anxiety, the most commonly measured
outcome type (k ⫽ 12), was associated with the strongest effect,
g ⫽ 3.11, SE ⫽ 0.38, 95% CI [2.368, 3.849], Z ⫽ 8.23, p ⬍ .001.
Publication Bias
A potential source of bias in meta-analyses is publication bias,
the potential for studies with significant results to be more abundant in the published literature and more easily located by re-
Table 3
Results of Categorical Moderator Analyses Using Mean Outcomes for Participants
Category
Intentionality, Q(1) ⫽ 2.73, p ⫽ .098
Intentional
Unintentional
Pre- or post-September 11, Q(1) ⫽ .41, p ⫽ .523
Pre-September 11
Post-September 11
Media format, Q(2) ⫽ 5.15, p ⫽ .076
Video
Print
Static images
Global location, Q(3) ⫽ 36.17, p ⫽ .000
U.S.
Middle East
Europe/Great Britain
Australia
Sensitization, Q(1) ⫽ 18.54, p ⫽ .000
Yes
No
Study design, Q(2) ⫽ 40.03, p ⫽ .000
Pre–post, no control group
Random assignment, post only
Random assignment, pre–post
g
95% CI
Z
p
k
1.939
.686
[1.289, 2.588]
[.650, 2.022]
5.85ⴱ
1.01
.000
.315
14
3
1.134
1.699
[⫺.490, 2.758]
[1.097, 2.301]
1.37
5.53ⴱ
.171
.000
2
16
2.229
.642
.965
[1.478, 2.979]
[⫺.748, 2.032]
[⫺.460, 2.390]
5.82ⴱ
.91
1.33
.000
.366
.184
11
3
3
.299
4.087
.744
.607
[⫺.676, 1.275]
[3.115, 5.060]
[⫺.167, 1.656]
[⫺1.549, 2.764]
.60
8.24ⴱ
1.60
.55
.548
.000
.109
.591
5
6
6
1
2.702
.356
[1.972, 3.432]
[⫺.424, 1.136]
7.26ⴱ
.89
.000
.371
10
8
.556
.519
4.066
[⫺.875, 1.987]
[⫺.140, 1.178]
[3.147, 4.985]
.76
1.54
8.67ⴱ
.446
.123
.000
2
10
6
Note. g ⫽…
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