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SOLUTION AT Academic Writers Bay 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: [email protected] 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 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. 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. 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. 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 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. 320 HOPWOOD AND SCHUTTE MEDIA EXPOSURE TO LARGE-SCALE VIOLENCE 321 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. 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 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. 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] 5.85�� 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 ⫽ point estimate of the effect size (Hedges’ g), using the mean of outcomes reported; CI ⫽ confidence interval; the 95% lower and upper limits of g; Z ⫽ z test for g; k ⫽ the number of studies associated with the g value; Q ⫽ test statistic that determines whether the effect varies significantly between the subcategories of the moderator variable (random effects model used). ⴱ p ⬍ .05. MEDIA EXPOSURE TO LARGE-SCALE VIOLENCE 323 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. Table 4 Outcome Type Moderator Analysis With Multiple Outcomes for Some Participants Category g 95% CI Z p k Outcome type (total k ⫽ 45), Q(4) ⫽ 24.65, p ⫽ .000 State anxiety Negative affect Perceived threat Other negative outcome Positive outcome 3.11 .86 .60 2.27 1.63 [2.368, 3.849] [⫺.553, 2.263] [⫺.162, 1.371] [1.516, 3.032] [.805, 2.447] 8.23ⴱ 1.19 1.55 5.88 3.88 .000 .234 .122 .000 .000 12 3 10 11 9 Note. g ⫽ point estimate of the effect size (Hedges’ g); CI ⫽ confidence interval; the 95% lower and upper limits of g; Z ⫽ z test for g; k ⫽ the number of outcomes associated with the g value; Q ⫽ test statistic that determines whether the effect varies significantly between the subcategories of the moderator variable (random effects model used). ⴱ p ⬍ .05. searchers than studies reporting no effects (Borenstein et al., 2009; Cooper, 2010; Rosenthal, 1979). To check for publication bias, Duval and Tweedie’s (2000) trim and fill procedure with funnel plot and a classic fail-safe N test (Rosenthal, 1979) were conducted using CMA. The funnel plot showed little asymmetry, and Duval and Tweedie’s trim and fill found no missing studies to the left of the mean, indicating no likelihood of publication bias. The failsafe N value (1,681) far exceeded the minimum recommended critical value of 100 (given by 5k ⫹ 10, where k is the number of studies in the meta-analysis; Rosenthal, 1991). This suggests that one would need to add 1,681 studies that found no effect of media exposure on psychological outcomes to render the effect nonsignificant. Given these findings, there is no evidence of publication bias. Discussion A large meta-analytic effect size showed that, across experimental studies, media exposure to disasters and large-scale violence resulted in increased negative psychological outcomes. This result, supporting the main hypothesis of the meta-analysis, suggests that such media exposure results in negative psychological outcomes. The finding of a causal impact across experimental studies adds to previous findings generated by correlational and longitudinal studies. Of the categorical moderators of effect size examined, community sensitization, global region, outcome type, and study design all had significant associations with negative psychological outcomes. For continuous moderator variables, percentage of females and reliability of outcome measures both reached significance. No statistically significant differences were found for the other moderator variables. Hypothesis

2, that media portrayals involving intentionality result in stronger negative psychological outcomes, was not supported, even though there was a weak trend toward significance, with intentionally caused disaster or violence having a larger effect. Hypothesis 3, that video portrayal results in larger effect sizes, also was not significant, but trended toward significance, with video footage evoking a stronger negative psychological outcome than print or static images. This trend is consistent with previous research supporting the ability of video to imbue the consumer with a more emotionally arousing experience and per- haps a potent communication of threat (Callahan et al., 2005; Cho et al., 2003). Hypothesis 4, that post-September 11 studies would show larger effect sizes, was not supported. Hypothesis 5 focused on community sensitization, in that we expected that studies conducted in areas recently experiencing large-scale disaster or violence show larger effect sizes. Analysis of the moderator variable community sensitization showed that effect sizes were significantly larger for studies conducted in a region that had recently been exposed to the type of disaster or threat portrayed in the media. This finding further bolsters the theory of cumulative adverse effects, in line with the conservation of resources theory, and is also consistent with research on complex trauma and poly victimization. A study conducted by Turner, Finkelhor, and Ormrod (2010) indicated that multiple incidences of trauma for children (across varying types of victimization) was linked to adverse psychological outcomes. The results suggested that cumulative episodes of adversity may be more strongly related to negative outcomes than are single events or even repeated occurrences of the same type of trauma. If, as the current results suggest, media coverage of disasters and traumatic events has the potential to cause transient negative psychological changes in individuals, then it is possible that cumulative effects over time (or intense prolonged exposure) may generate more serious adverse outcomes. Related to the community sensitization hypothesis, effect sizes varied across global regions. Studies conducted in the Middle East showed much higher effect sizes than studies from other regions. Given the historical incidences of war and terrorist attacks in this region (Solomon, Gelkopf, & Bleich, 2005), these results suggest that the cumulative effects of this type of trauma may render people more susceptible toward negative reactions to media exposure to disaster and large-scale violence. Again, this is consistent with previous research showing that multiple stressors over time or a history of trauma may render people more vulnerable to mental health disorders such as PTSD and anxiety or mood disorders (Brewin et al., 2000; Myers et al., 2015). Similarly, a metaanalysis of studies examining the behavioral consequences of terrorism showed that a history of diagnosed mental health problems was strongly associated with PTSD following a terrorist incident (DiMaggio & Galea, 2006). 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. 324 HOPWOOD AND SCHUTTE Hypothesis 6, predicting that studies with a higher percentage of females show larger effect sizes, was not supported. In the current study, the metaregression using percentage of females as a covariate provided a statistically significant model, but the association was small and not in the expected direction. This is not consistent with gender effects having been found frequently in previous research (e.g., Baum et al., 2014), with females found to be more at risk of adverse outcomes related to media exposure and to other forms of indirect exposure to trauma. Future research might further explore the effect of gender on reaction to media exposure.

Hypothesis 7 predicted that studies with older participants or child participants would show stronger effect sizes. The metaregressions for mean age— using both linear and curvilinear models— did not reach significance. As a group, children were underrepresented in the meta-analysis, with only two studies using child participants. Similarly, older adults were not well represented, with the highest mean age for a study being 41.47. Given this lack of variability in mean age, these findings should be interpreted with caution. These results can be viewed in the context of previous research that has presented mixed results regarding age effects on outcomes relating to media and other forms of indirect exposure to trauma (e.g., Kun et al., 2009; Shrira et al., 2014). Exploratory moderator analyses investigated effects for different outcomes and aspects of methodology. The included studies measured a variety of psychological outcomes. State anxiety was the most measured and strongest outcome. This result is consistent with correlational research reporting a link between media consumption of disaster-related content and anxiety (Cohen et al., 2006; Schlenger et al., 2002; Schuster et al., 2001; Sugimoto et al., 2013). The overall effect size for perceived threat was not significant, which is inconsistent with many previous correlational research findings (Fahmy & Johnson, 2007; Nabi & Sullivan, 2001; Nellis & Savage, 2012; Ridout, Grosse, & Appleton, 2008) and what would be predicted based on protection motivation theory. One possible explanation for this may be the laboratory conditions attached to the studies; perhaps the artificial environment reminded participants that the media content was not necessarily temporally or personally relevant. Thus, although the media content may have evoked negative emotions and anxiety, a perceived lack of personal involvement or perceived reality may have reduced estimations of threat (Roser & Thompson, 1995; Wilson, 2008). In relation to methodology, both study design and reliability of measures were significant moderators. Studies with random assignment to groups and pre–post measurement showed stronger effect sizes. Studies using measures with greater reliability showed stronger effect sizes. These results suggest that the more exact the methodology, the larger the effect sizes, and bolster confidence in the overall effect found in the meta-analysis. The findings of the current study partially support the proposed theoretical framework based on protection motivation theory and conservation of resources theory. As predicted by protection motivation theory, the significant and strong overall effect size for state anxiety is consistent with expectations of anxiety and stress arising in the wake of threatening events. However, the failure of the overall effect size for perceived threat to reach significance is inconsistent with a model of perceived threat being a necessary precursor to anxiety. This suggests that there are additional path- ways between the consumption of the media report and feelings of anxiety or stress. An improved conceptual framework might include mechanisms such as emotional contagion—the process whereby individuals tend to unconsciously mimic the affect of others, producing an authentic subjective experience of the emotion (Hatfield, Cacioppo, & Rapson, 1993). Watching the suffering of other people may evoke feelings of empathy and identification, thus facilitating the process of emotional contagion, evoking feelings of anxiety and stress to mirror those of depicted victims (Nummenmaa, Hirvonen, Parkkola, & Hietanen, 2008). Conservation of resources theory predicts that a cumulative burden of adversity will diminish an individual’s perceived store of psychological resources and increase vulnerability to future trauma. This part of the conceptual framework was supported by the current results relating to community sensitization and is consistent with recent findings regarding complex trauma and poly victimization (Turner et al.

, 2010). These findings support the possibility of negative outcomes amassing in individuals as the result of repeated exposure to media reports of disasters or largescale violence. Limitations A large number of data sets were provided by two teams and, although we took care to ensure that the data sets themselves were independent, the results should be interpreted with caution. It should be noted that the largest effect sizes appear to be impacted by the moderator variables shown to be associated with greater effects (e.g., Middle East location, intentional acts, video presentation, community sensitization), a pattern that is consistent with our major findings. When considering the results from the different teams, it may be useful to be mindful of the significant differences between the populations studied. The lack of studies in some subgroups meant that several moderator analyses lacked statistical power and thus may have failed to detect real differences. For example, in relation to the preor post-September 11 moderator, only two studies were conducted before September 11. Most of the studies included in the metaanalysis were conducted in laboratory settings, used one-time exposure to the stimulus material, and measured immediate psychological outcomes. Although this methodology is beneficial in terms of minimizing the influence of confounding variables, it reduces ecological validity. People may have different reactions in real-world situations because of autonomy in selection of media content, social support, and a myriad of other variables that may affect outcomes. The included studies examined only short-term effects of trauma-related media exposure. Longer detrimental (or beneficial) outcomes were not assessed because of the time-limited nature of the experimental designs used. Thus, it is unknown how transient or enduring these effects may be. Research Implications Future experimental studies with a longitudinal component could assess the longevity of psychological responses to media exposure, particularly cumulative effects. Future studies might also identify groups at risk for intense or longer lasting effects, including potential effects for children and elderly adults. Finally, MEDIA EXPOSURE TO LARGE-SCALE VIOLENCE future studies might investigate the impact of understudied media modalities, such as audio presentations, and emerging future modalities, such as virtual reality presentations. 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. Clinical and Policy Implications In conjunction with correlational research linking media consumption with anxiety, posttraumatic stress symptoms, stress reactions, depression, anger, and fear (Houston, 2009; Pfefferbaum et al., 2014), the results of the present meta-analysis of experimental studies suggest that media consumption can be a source of psychological distress. Clinicians might consider discussing media consumption with distressed clients to assess whether types of media viewed may be a source of distress for clients. Media professionals might consider the impact of media coverage on consumers, especially on viewers who might be sensitized to experience negative reactions, particularly viewers in areas experiencing disasters or violence such as that portrayed in the media coverage. Conclusion People have more access than ever before to graphic media coverage of disasters and large-scale violence. Given the ubiquitous nature of bad news in the modern world, it is important to understand the psychological outcomes associated with exposure to this type of media. The results of the current meta-analysis suggest that media exposure to disasters or large-scale violence plays a causal role in negative psychological outcomes, at least transiently. Further, people in communities with a recent history of disaster

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, Ben-Zur, H., & Reshef-Weil, S. (2011). Vicarious life threat: An experimental test of conservation of resources (COR) theory. Personality and Individual Differences, 50, 641– 645. http://dx.doi.org/10 .1016/j.paid.2010.11.035 Received September 28, 2015 Revision received March 18, 2016 Accepted March 18, 2016 䡲 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: [email protected] 123 718 D. E. Alexander 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. 123 Social Media in Disaster Risk Reduction 719 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). 123 720 D. E. Alexander 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 123 Social Media in Disaster Risk Reduction 721 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 123 722 D. E. Alexander 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, 123 Social Media in Disaster Risk Reduction 723 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 123 724 D. E. Alexander 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 informat… CLICK HERE TO GET A PROFESSIONAL WRITER TO WORK ON THIS PAPER AND OTHER SIMILAR PAPERS CLICK THE BUTTON TO MAKE YOUR ORDER Related posts: (Q) psychology psychological aspects of disaster (Mt) – Colorado Christian University Wk 12 Disaster Behavioral Health Questions Taif University Disaster Mental Health Discussion Response (Mt) – University of Arizona Stakeholder Management Discussion Questions

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