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12 | Briefings on Hospital Safety July 2018

These workers, says OSHA, must be trained by a qualified person to correctly identify and minimize fall hazards; use personal fall protection systems and rope descent systems; and maintain, inspect, and store equipment or systems used for fall protection.

When there is a change in workplace operations or equipment, “or the employer believes that a worker would benefit from additional training based on a lack of knowledge or skill, then the worker must be retrained,” states OSHA materials. The training must be provided in a language and vocabulary that workers understand.

Remember to include falls safety when hiring a con- tractor to do work at your facility. Under OSHA’s multi-employer citation policy, it is possible for your

hospital as well as the contractor or subcontractor to be cited for an unsafe workplace or incident in which someone is injured or killed.

When dealing with a contractor, OSHA will expect a hospital to create a site-specific safety program, supervise and enforce the safety protocols for that project, and maintain authority to correct safety hazards, Salmasi says. Have regular safety meetings with contractors and subcontractors, document those meetings, and do regular inspections on-site, he recommends. H

EDITOR’S NOTE:

A version of this story first appeared in Environment of Care Leader,

a DecisionHealth newsletter.

HEALTHCARE SECURITY ALERT

Active shooters

Five key steps for creating, implementing an active shooter plan at your healthcare facility The threat of an active shooter roaming the hallways is one of the biggest worries among safety professionals and C-suite executives in the health- care industry.

Preparedness for active shooter situations is also on the minds of accrediting organizations and agencies such as CMS, The Joint Commission, NFPA, and OSHA, who have all recently called for better protection of healthcare workers from workplace violence or are currently considering new standards.

Steve Wilder, BA, CHSP, STS, has spent more than three decades in healthcare safety, security, and risk management, including stints as a hospital

risk manager and corporate director of safety and security for a health system. He has consulted with hundreds of clients, including hospitals, clinics, and physician practices, and has trained thousands of workers in workplace safety and security.

In addition to his regular contributions to health- care magazines, Wilder co-authored the book The Essentials of Aggression Management in Healthcare: From Talkdown to Takedown.

During a December 2017 webinar organized by HCPro, Wilder explained how to comply with the revised CMS rule for emergency preparedness and prepare your staff for any situation. He also helped attendees understand the key parts of an active

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HEALTHCARE SECURITY ALERT

shooter plan, went over how staff can improve deci- sion-making skills, and provided tips on controlling staff anxiety and stress during emergency situations.

In this 90-minute webinar—which can be viewed on demand through HCMarketplace.com—he shared his five key components for an active shooter plan. The following is a summary of that portion of Wilder’s presentation.

Step 1: Conduct a vulnerability assessment

Wilder believes the first key component of an active shooter plan is determining threats. Who might pose internal or external threats to your building or campus? How can you assess vulnerabilities that “are the chinks in the armor that allow an opportu- nity for a bad guy to strike”? Then you should consider the potential outcomes if an active shooter were to barge into your healthcare facility.

As a consultant, Wilder routinely does vulnerabil- ity assessments for healthcare organizations.

“We come in from the outside and see the things you see every day to the point where you stop seeing them,” he said. “I tell my clients, ‘We’re good guys that get paid to look like bad guys.’ ”

Wilder said that for an active shooter event to occur, three critical factors must be present.

“First of all, there has to be a bad guy. The bad guy is always going to be a part of our society. There’s nothing we can do to get rid of him. We can put one in jail and there will be 10 more stepping up to take his place,” said Wilder. “Secondly, the bad guy has to have a motive. I can’t do anything about the motive. That comes from inside his heart or inside his head.”

He continued: “And thirdly, he has to have an opportunity. … The only thing we can do is take away his opportunity to strike at our place, whether it’s a burglar or an active shooter or an

arsonist, a predator, whatever the case may be. The only thing we can do is take away his opportunity, and that’s what the security vulnerability assess- ment is designed to do.”

After identifying all the opportunities “for the bad guys to strike,” steps can then be taken to put programs in place “to minimize the vulnerabili- ties,” which, said Wilder, is “a great step.”

Step 2: Develop an emergency response plan

Wilder said an active shooter emergency response plan must keep in mind everyone who could come through your doors—including but not limited to patients, employees, residents, visitors, and ven- dors. “We’ve got to incorporate all those people in, because when we’ve got an active shooter in the building, we become responsible for all those people,” he said.

Wilder notes that writing an active shooter emer- gency response plan “is much more challenging in our buildings than it is in any other industry because a lot of our doors” can’t have locks.

And, he said, that plan “has to be realistic to the threat,” whether the shooter is looking for a specific person such as an ex-spouse, or whether the situa- tion is like “in San Bernardino a couple of years ago where the individual just wanted to spray bullets and he doesn’t care how many people he takes out.”

Regardless of a shooter’s motive, the plan should be written “with a survival mindset.”

“This is the one emergency code that is not going to involve a response team,” said Wilder. “When you have an active shooter, you’re not going to have a code team responding. People need to be run- ning the other way. If you’re involved in this scenario, that puts you in a position of having to rely on yourself for survival—ergo relying on your training for survival.”

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14 | Briefings on Hospital Safety July 2018

Wilder added, “We can be sitting ducks if we don’t have a plan.”

Whoever is writing your active shooter emergency response plan should be thinking of the answers to critical questions such as “Where are the exits?” and “Where are my hiding places?” as well as “Where are my weapons of opportunity to protect myself if I have to fight back?”

Wilder teaches a model called the “Four Outs,” which he called “ ‘Run, Hide, Fight’ on steroids,” and he discussed it in detail during the webinar. But perhaps the biggest difference between “Four Outs” and the “Run, Hide, Fight” model, which was developed by the Department of Homeland Secu- rity, is that the former considers options for setting up barricades in rooms with doors that don’t lock.

Step 3: Develop an active shooter training program

Once the written plan is completed, then you can develop your training program, said Wilder. Plan and program must be consistent, he stressed, because “catastrophic outcomes will result” if your written plan tells your employees to do one thing and the training program says something different.

He cautioned against buying a prewritten active shooter emergency response plan and training program online because they will not be tailored for your individual facility.

“Every one of you has different points of access. Every one of you has different hours that your perimeter doors are locked and unlocked. Every one of you has different visitor standards. Every one of you is different,” he said. “Why would you want to try to buy a generic plan that’s written one size fits all? It doesn’t work. You have to write your plan specific to your facility.”

HEALTHCARE SECURITY ALERT

Wilder recommends a four-step approach to training, starting with awareness, then preparedness “where we actually train on the content of our plan,” then exercises and drills. Last but not least, the fourth step is evaluating your plans and looking for ways to improve them.

“At the end of every exercise, we need to look in the mirror and say, ‘How did we do?’ ” said Wilder. “We’ve got to improve. This is a continuous quality improvement process.”

He added that training must be “all-inclusive”—yes, administrators and C-suite executives, too. And that’s not just because surveyors will hit you with a major citation if they discover executives skipped the training.

“Number one, just because you’re in the C-suite, you’re not immune to training,” he said. “Number two, as part of the chief executive branch, people are looking to you for leadership, and if you are not trained in the same program that your people are trained in, you’re going to be telling them to do one thing when your plan says something else —in the worst possible situation.”

Step 4: Train staff how to respond to an active shooter

After finishing an active shooter training plan that fits seamlessly with the emergency response plan, it’s time to actually start using it to train your employ- ees. Wilder said that all new employees should go through a facilitywide program as well as depart- ment-specific training.

Wilder believes employees should be trained to pick the best course of action from a range of options, so they can make the safest decision as quickly as possible. “And we want to make sure that they know how to apply those choices and when to make [each] choice,” he said.

He said that in a real-life active shooter situation, the first responses for everyone, including a trained

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HEALTHCARE SECURITY ALERT

that to prepare me so that in the event of an emergency

situation—when my adrenaline is skyrocketing, and

my pulse is racing and I’m hyperventilating probably,

I’m not thinking clearly and my mind isn’t working

properly—they want those responses to become

second nature.”

Step 5: Plan for the response after an emergency

In the aftermath of an active shooter event, you

must quickly initiate a facility crisis management

plan to return to a normal—and safer—state of

affairs as quickly as possible. Among the many

needs at that time may be a liaison to the media,

additional security, and crisis counseling.

The hours and days after this kind of emergency

will be chaotic, so plan ahead, said Wilder.

“At 1 o’clock in the morning when the shooting has

taken place is not the time for me, with shaking

hands and total anxiety, to be flipping through the

yellow pages looking for a crisis counselor or

additional security or whatever I need,” said

Wilder. “I need to do my planning in advance.”

safety and security professional like himself, would be “startle and fear.”

“And that’s OK,” he said. “Guys, this is scary. It’s OK to be scared, even if you’re well-trained.”

But what happens next, Wilder said, usually depends on an individual’s level of training.

“All that training is going to come back to the forefront of your head, and your response is going to be exactly what you were trained to do,” he said. “It’s amazing. I’ve seen it over and over and over. Your training kicks in. You might have forgotten everything about that training program, but your brain—that big hard drive in your head—all of the sudden brings it back to active memory.”

And if staff haven’t been trained? “They’re going to have a meltdown on you. They’re going to be useless. They’re going to be a liability to you and they’re going to get you hurt or killed.”

That’s why he scoffed at the thought of “people being scared to do these exercises.”

Wilder compared it to monotonous pre-flight instruc- tions from flight attendants, saying, “They’re doing

Security

Use new NFPA 3000 to improve community planning for mass casualty response Use a new NFPA standard to review your over- all preparedness for responding to mass casualty events and improve your coordination with other healthcare providers, first responders, and commu- nity emergency organizations.

Spurred by coordination problems identified after several recent mass shootings, NFPA 3000, a Stan- dard for an Active Shooter/Hostile Event Response

(ASHER), is designed to help communities prepare for multiple casualties. It was released May 1.

There is no current mandate for hospitals to embrace the standards set out in NFPA 3000, which was fast-tracked as a provisional standard in the aftermath of the mass shooting at an Orlando, Fla., nightclub in June 2016 (ECL 5/7/18). However, both CMS and The Joint Commission have noted

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Mental Health Organizations Module 12

Resource Mission

• Practitioners

• Educators

• Students

• Clients

• Families

Advocacy Education

Research

American Psychological Association (APA)

All Psychology Topics

• Abortion

• Addictions

• ADHD

• Aging

• Alzheimer's

• Anger

• Anxiety

• Autism

• Bipolar disorder

• Bullying

• Children

• COVID-19

• Death and dying

• Depression

• Disability

• Disasters

• Eating disorders

• Education

• Emotional health

• Environment

• Ethics

• Hate crimes

• Health disparities

• HIV and AIDS

• Human rights

• Hypnosis

• Immigration

• Intelligence

• Kids and the media

• Law and psychology

• Learning and memory

• Lesbian, gay, bisexual, transgender

• Marriage and divorce

• Military

• Money

• Obesity

• Pain

• Parenting

• Personality

• Posttraumatic stress disorder

• Racism, bias, and discrimination

• Safety and design

• Schizophrenia

• Sex

• Sexual abuse

• Shyness

• Sleep

• Socioeconomic status

• Sport and exercise

• Stress

• Suicide

• Teens

• Testing issues

• Therapy

• Trauma

• Violence

• Women and men

• Workplace issues

American Psychiatric Association

National Institute on Mental Illness (NIMH)

National Institute on Mental Illness (NIMH) – Part 2

National Alliance on Mental Illness (NAMI)

Substance Abuse and Mental Health Services Administration (SAMHSA)

Things to consider:

Create a resource listCreate

Contact referral sources

(psychiatrist, psychologist, therapist, social workers, drug treatment programs, etc. ) Contact

Identify contacts in local offices of national organizations (NIH, APA, NAMI, etc)Identify

End of Presentation

CHAPTER 12

Mental Health Organizations

Copyright © 2021 by Jones & Bartlett Learning, LLC an Ascend Learning Company. www.jblearning.com

Training for the Unthinkable: Examining Message Characteristics on Motivations to Engage in an Active-Shooter Response Video Jessica L. Ford & Seth S. Frei

Campus safety is becoming an increasing concern for academic institutions due to numerous recent tragedies. To prepare students, staff, and faculty for these events, schools are beginning to use active shooter response training videos such as Run, Hide, Fight—a 5-minute video created by the U.S. Department of Homeland Security. Framed in protection motivation theory, this study employs a 3 x 2 factorial design to test the influence of message medium (email, text, or tweet) and frame (direct or fear- based message) on students' completion of the safety training video. The findings suggest that the combination of message frame and message medium influence training com- pletion. Additionally, the video itself led to a significant increase in participants’ self- efficacy, safety knowledge, and campus safety salience.

Keywords: Campus Safety; Protection Motivation; Safety Training; School Schootings

Unthinkable tragedies are occurring on our nation’s campuses at a frightening frequency (Midlarsky & Klain, 2005). The rise in school shootings in America has sparked a particular focus on protecting and planning for these events (Kingshott & McKenzie, 2013). In fact, according to the Jeanne Clery Disclosure of Campus Security Policy and Campus Crime Statistics Act (20 U.S.C. § 1092(f), 1999), all higher education institutions actively accepting government funds are required to put in place emergency response plans. An integral part of preparing for these events

Jessica L. Ford is an Assistant Professor in the School of Communication Studies at Ohio University. Seth S. Frei is a Lecturer in the Department of Communication Studies at Texas State University. Correspondence: Jessica L. Ford, School of Communication Studies, Ohio University, 400 Schoonover Center, 20 E. Union, Athens, OH 45701, USA. E-mail: [email protected]

Communication Studies Vol. 67, No. 4, September–October 2016, pp. 438–454

ISSN 1051-0974 (print)/ISSN 1745-1035 (online) © 2016 Central States Communication Association DOI: 10.1080/10510974.2016.1196381

from a safety-personnel perspective is the training of civilians to react effectively to these emergencies (Kingshott & McKenzie, 2013). Despite the considerable need to train our schools’ students, staff, and faculty for these events, few studies have examined the effectiveness of organizational training initiatives (see Sattler, Kirsch, Shipley, Cocke, & Stegmeier, 2014 for a notable exception).

In many cases, campuses simply offer information about how to respond to an active-shooter situation through a Web site, brochure, video, or e-mail. Thus, under- standing proper emergency response behavior is placed on the individual’s motivation to learn this vital information on his or her own time (Sattler et al., 2014). Clearly, there are inherent problems with this design. For instance, if those on campus are unaware of these training materials, the influence of this information is limited. Besides the need to effectively promote active-shooter response-training programs, campuses must work against the dominant belief that the likelihood of these events occurring is slim-to-none. Time and again, this is the overwhelming response from those affected by school shootings (Oksanen, Räsänen, Nurmi, & Lindström, 2010).

RESEARCH OBJECTIVES

Recognizing that schools must prepare their students, faculty, and staff for potential active-shooter emergencies, the present study focuses on the effectiveness of messages prompting the completion of a safety training video. The first goal of this study is to understand which media—e-mail, text, or Twitter—and which message frame—fear- based or direct information—are most effective on messages designed to promote participation in an active-shooter response-training initiative. The second objective of this study is to test the impact of this training video on participants’ (a) safety knowledge, (b) safety self-efficacy, and (c) personal campus safety salience. We define personal campus safety salience as an individual’s active concern for their safety at school. For instance, someone who has a high level of personal campus safety salience may avoid areas of campus due to safety reasons, or even worry about an active shooter event happening at his or her school. Taken together, understanding the effectiveness of different media used to promote participation in training, as well as the impact of these videos, carries important implications for all academic institutions plagued by the fear of these potential events. The following sections describe the guiding theoretical framework in detail and provide a review of literature on message characteristics, threat appraisal, and coping appraisal.

PROTECTION MOTIVATION THEORY AND ACTIVE-SHOOTER RESPONSE TRAINING

Protection motivation theory (PMT) helps explain why people respond to similar threats differently (Rogers, 1975). The extensive use of PMT as a framework in health studies for assessing how individuals decide to make behavioral modifications to either promote or suppress their well-being (e.g., Gaston & Prapavessis, 2012) lends

Message Characteristics and Protection Motivation 439

itself well to studying safety-related messages. As such, this framework is especially useful in understanding the cognitive process that mediates the response to fear-based messages, where individuals assess the severity of a threat and their ability to cope with it. Rogers (1975) offers three phases of protection motivation, where individuals (a) evaluate the information they know about the threat, (b) appraise the severity and their ability to cope with the threat and (c) decide to either respond in an effective or ineffective manner (see Figure 1). All three of these processes are important in assessing how the same fear-based stimuli can produce vastly different responses.

The first component of PMT is the assessment of both environmental and intra- personal factors that relate to the threat (Rogers, 1975). The environmental factors include what someone hears from others about the likelihood of the event as well as their observations of potential hazards or threats (Floyd, Prentice-Dunn, & Rogers, 2000). In relation to protection motivation against school shootings, students may hear others (i.e., faculty, parents, or peers) talk about national events and subsequently have concern for their campus. Students may also observe an increase in safety-related features around campus (e.g., blue-light warning systems, emergency-siren installa- tion, and availability of mental-health services) in response to the rise in school shootings. Beyond environmental considerations, PMT states that intrapersonal fac- tors, such an individual’s personality and prior experience with the threat, affect the cognitive-mediating processes for protection motivation (Rogers, 1975). Referring to school safety, students may have prior experience with an active shooter on campus or know someone that has been affected by a similar event (Floyd et al., 2000).

In the PMT model, the environmental and interpersonal factors are the primary sources of information used to assess the credibility of the threat. This makes sense given that this model is nearly 40 years old. In light of the myriad media and sources available today, we consider two additional message characteristics in assessing the credibility of a threat. In particular, we focus on how the message medium (e.g., e-mail, text, or Twitter), and message frame (e.g., fear-based or direct information) of announcements encouraging participation in such training initiatives impact safety- training completion. In addition, we examine how the video itself affects participants’ safety knowledge, safety self-efficacy, and personal campus safety salience.

Figure 1 Rogers (1975) original model of protection motivation

440 J. L. Ford & S. S. Frei

The threat and coping appraisal involves three components that Rogers (1975) believes happen simultaneously. According the theory, an individual will assess the perceived magnitude of the threat, the probability the event will occur if no preventa- tive action is taken, and the extent of an individual’s response efficacy at the same time. Floyd and colleagues (2000) describe response efficacy as “the belief that the adaptive response will work, that taking the protective action will be effective in protecting the self or others” (p. 411). As the mediating processes that impact an individual’s coping response, these items each play an important role in the appraisal stage. Though each aspect of the appraisal is important, when applied to active- shooter response training, we believe individuals will assess the perceived severity and likelihood of an active-shooter event on their campus before evaluating their perceived ability to respond effectively.

The final phase of protection motivation theory is the decision to adapt to the situation either through an effective or ineffective behavioral change (Rogers, 1975). For instance, in relation to the present study, an effective reaction to the message promoting the active-shooter response training is the completion of the training video. Additionally, an effective response is measured by an increase in one’s (a) safety knowledge, (b) safety self-efficacy, and (c) personal campus safety salience. Contrarily, participants who stop watching the video early, or choose to click past it altogether, constitute an ineffective response to the initial message.

The validity of PMT as a framework for research is demonstrated through its extensive use in studies addressing health-based threats and responses (see Frisby, Veil, & Sellnow, 2014; Lwin, Stanaland, & Chan, 2010, for notable examples). Thus, using PMT to guide research on the effectiveness of fear-based messages promoting active-shooter response training preserves both the integrity of the theory and our research. The present study employs PMT as a framework for understanding why individuals decide to complete this training while others do not. Using PMT, we first discuss the importance of message characteristics in evaluating threat credibility.

Message Characteristics

The reason why individuals may respond differently to messages that encourage them to participate in training for an active shooter may be due, in part, to the message characteristics. Previous research on safety-message characteristics advances the idea that source credibility and message framing are integral aspects of a message’s persuasive capacity (Sattler et al., 2014). For instance, Sutton and colleagues (2015) found that Tweets during the 2013 Boston Marathon Bombing were most likely to be passed along to others if they contained emotional, evaluative, or prescriptive content. In relation to the present context, research on campus safety finds that effective message placement, speed, and character- istics are essential for effective postevent notifications (Lachlan, McIntyre, & Spence, 2016; Lachlan & Spence, 2014). While prior research advances our understanding of the role message characteristics play during emergency

Message Characteristics and Protection Motivation 441

situations, less is known about the influence of message frames and media on promoting the completion of safety-training initiatives prior to an emergency. As such, we extend the present literature by focusing on the impact of source credibility and message framing on training completion, campus safety salience, safety knowledge, and self-efficacy.

Source credibility Source credibility is defined as the “judgments made by a perceiver concerning the believably of a communicator” (O’ Keefe, 2002, p. 181). While the study of credibility has shaped the development of the academy since ancient Greece (Aristotle, 1954), the proliferation of sources now available at our fingertips calls for a reexamination of this construct (Rains & Karmikel, 2009). Recent research indicates that social-media platforms (i.e., Twitter) produce higher levels of infor- mation trust due to the nature of the shared network (Crowe, 2011). As a result, many organizations use social media as a way to connect and communicate with their stake holders in order to build trust. In fact, the Federal Emergency Manage- ment Agency has an active Twitter account and uses it to communicate urgent information (Wukich & Steinberg, 2013).

Yet, more traditional forms of distributing training-related information to organi- zational constituents are still relevant. Although social-media platforms can have a wide reach (Vieweg, Hughes, Starbird, & Palen, 2010), they require individuals to sign up and have been attributed with spreading false information, which may decrease the credibility of this medium (Mendoza, Poblete, & Castillo, 2010). In addition, not all organizational members may be active users of these tools. Thus, the use of organiza- tion-wide e-mails and text messages are still used for distributing information about emergency training programs. In addition to source credibility, the frame contributes to the characteristics of the message.

Message Framing When an individual sends a message to someone, the words and descriptions they use help frame the idea. Research on the effectiveness of fear-based appeals on subsequent behavior is inconsistent. On one hand, fear-based appeals are shown to encourage healthy behaviors (Nan, Xie, & Madden, 2012). Contrarily, some scho- lars indicate that fearful frames on health-related messages have the opposite intended effect (Brennan & Binney, 2010). Considering the potential implications of active-shooter response-training videos on improving campus safety, we manip- ulate message framing in our experimental design in order to see if it impacts the completion of the training video. Beyond looking at the message framing, there are additional factors that may alter an individual’s motivation to complete the training for an active-shooter emergency. According to PMT, the two components of the cognitive-mediating process, threat and coping appraisal, are important considerations.

442 J. L. Ford & S. S. Frei

Threat and Coping Appraisal

The reasons why individuals decide not to evacuate in a flood (Dash & Gladwin, 2007) may be similar to the reasons why some individuals may not complete a potentially life-saving training video on responding to an active shooter. According to PMT, individuals will assess the threat and their ability to cope with it before altering their behavior (Rogers, 1975). For the present study, the threat appraisal is measured by an individual’s personal campus safety salience. This is an individual’s active concern for their safety on campus. The trend of school-shooting assailants employing public media to broadcast their justification for their attacks perpetuates a national preoccupation with fear (Altheide, 2009). For instance, both the Virginia Tech and University of California Santa Barbara shooters created a YouTube video that warned of their attacks just minutes before they began their killing rampage (Lindgren, 2011). Few researchers have sought to measure the impact of school shootings on student fear, but recent research after Virginia Tech indicates that this event produced an increase in student fear (Kaminski, Koons-Witt, Thompson, & Weiss, 2010). This heightened level of fear, which we refer to as personal campus safety salience, may motivate the participants in this study to complete the active- shooter response-training video.

Another factor to consider when examining how an individual perceives the threat of an active shooter on campus is their prior experience with a similar event. Whereas some researchers have found that prior victimization has no significant effect on one’s level of fear on campus (Jennings, Gover, & Pudzynska, 2007), others have found that the type of victimization (e.g., robbery versus sexual assault) does impact one’s perception of fear on campus (Wilcox, Jordan, & Pritchard, 2007). If an individual has experienced an active-shooter emergency, knows someone who has, or perhaps attends a school where there was a threat of an active-shooter event, he or she may have a heightened sense of fear toward these types of crimes. With this in mind, the present study controls for individuals’ prior experience in order to assess the true impact of the training video on personal campus safety salience, safety knowledge, and safety self-efficacy.

Lastly, the concept of self-efficacy has received considerable attention as a predictor of health-related behavioral change (Nabi & Thomas, 2013). Self-efficacy is generally defined as the perceived capacity to handle or cope with a given situation. In the present study, we refer to an individual’s judgment of their ability to have an adaptive response to a school shooting as safety self-efficacy. Research shows that resources (e.g., brochures, videos, Web sites) addressing the preparation for a school shooting help promote a sense of safety self-efficacy (Benight & Harper, 2002). However, scant research has addressed whether there is a particular type of media and frame that produces greater safety self-efficacy. Applying the literature of self-efficacy and source credibility, the present study begins to fill this research gap. Specifically, we offer several research questions directed toward examining the impact of the medium and frame used in promoting active-shooter safety-training initiatives.

Message Characteristics and Protection Motivation 443

RESEARCH QUESTIONS

Bearing in mind the implications of completing these potentially life-saving training videos, it is crucial for communication scholars to investigate how individuals interpret and respond to these messages. Framed in terms of PMT, the present study is concerned with the influence of media (i.e., e-mail, text, or Twitter) and message frame (i.e., fear-based or direct information) on the completion of an active-shooter response-training video. Furthermore, this study assesses the impact of the training video on participants’ (a) safety knowledge, (b) safety self-efficacy, and (c) personal campus safety salience. Previous research indicates that higher levels of fear arousal are more persuasive in motivating individuals to respond effectively (Rogers, 1975). We expect this finding to extend to the context of fear- based messages in this study, which encourage individuals to complete the active- shooter response-training video. However, the way a message is delivered though a particular medium may influence whether or not individuals decide to complete the training video. Additionally, the message frame and medium used may produce varying levels of change in all of our variables of interest. Based on the exploratory nature of this experiment, the following research questions are proposed:

RQ1: Which combination of message frame (fear-based or direct information) and message medium (e-mail, text, or Tweet) influences individuals to complete the training video?

RQ2: Which combination of message frame (fear-based or direct information) and message medium (e-mail, text, or Tweet) produces the greatest change in (a) personal campus safety salience, (b) safety knowledge, and (c) safety self- efficacy after individuals view the training video?

RQ3: Controlling for (a) prior campus safety experience, (b) having watched the video before the experiment, and (c) the treatment condition, does watching the training video change individuals’ safety salience, safety knowledge, or safety self-efficacy?

METHOD

To test the proposed research questions, we ran an experiment using a 3 x 2 factorial design. In the experimental conditions, we altered the message medium (e-mail, text, or Twitter), and frame (fear-based or direct information) in prompts encouraging students to watch a safety-training video. Regardless of the type of message the participants received, there was a pretest and posttest that measured their change in personal campus safety salience, safety knowledge, and safety self-efficacy. Addition- ally, we measured prior campus safety experience, prior viewing of the video, and extent of video completion. The following reviews the experimental conditions and participant pool in detail.

444 J. L. Ford & S. S. Frei

Participants

The sample for this study consisted of 242 undergraduate college students recruited from a large public university in the Southwest United States. Participants consisted of 14.5% (n = 35) males and 84.7% (n = 205) females with 0.4% (n = 1) choosing not to reveal their gender. The age of participants ranged from 18–34 (M = 20.3) and they represented all class levels at the university with 11.6% (n = 28) freshman, 18.2% (n = 44) sopho- mores, 40.5% (n = 98) juniors, 28.5% (n = 69) seniors, 0.4 % (n = 1) graduate students, and 0.4 % (n = 1) choosing not to answer. The video used in the experiment is available through the school’s campus safety and security Web site, but only 14.0% (n = 34) of the sample had seen it before, representing a small portion of the sample size.

Experimental Conditions

Each of the experimental conditions were created by the authors to replicate actual messages that a student could receive from the university. The first manipulation was the message media, which varied among the following three options: a formal university e-mail, text message, or an official university Tweet. All three of the conditions mirrored the university’s format and design to replicate the types of messages students actually receive. The second manipulation in the experiment was the frame of the message, which was either fear based or direct information. The frame was manipulated by adjusting the tone of the message. The direct-information e-mail condition read:

The university is dedicated to the safety and well-being of its students, faculty, and staff. Should an emergency occur on campus, we hope that you will take the appropriate protocol. Please watch the following 5-minute video, using the link below to prepare yourself in case of an active-shooter emergency on campus.

The frame of the second e-mail condition conveyed the same information but used a fear-based frame. The message stated:

In the past year, 68 school shootings have taken place on America’s schools and universities, leaving 65 dead, and dozens more injured. No one expects these incidents to happen at their school, but we must prepare for the unexpected. Please watch the following 5-minute video, using the following link to prepare yourself in case of an active-shooter emergency on campus.

Similar to the manipulation of the message frame for the e-mail, the Twitter messages were created using a fear-based or a direct-information frame, but these messages used less than 140 characters. The direct information Tweet stated, “Stay up to date on the universities safety protocol for an active-shooter emergency. Watch the following 5- minute training video.” The second Tweet conveyed the same information but used a fear-based frame and read “Since Sandy Hook, there have been 68 school shootings— leaving 65 dead and dozens injured. Prepare yourself for the unthinkable by watching the following 5-minute training video.” In addition to exploring the influence of the manipu- lated experimental conditions, we were also interested in examining the impact of the video intervention on campus safety salience, safety knowledge, and safety self-efficacy.

Message Characteristics and Protection Motivation 445

Video-Training Intervention

Run, Hide, Fight, is a training video for active-shooter response (Ready Houston, 2012). The video was produced by the U.S. Department of Homeland Security and the City of Houston Mayor’s Office of Public Safety in 2012. The video is 5-minutes long and contains high-intensity action training for individuals that might possibly be victims in active-shooter scenarios. The video follows the story of a typical office building that is overtaken by an active shooter. Throughout the video, viewers see at least three victims directly shot by the active shooter and they hear multiple other shots, presumably at other victims. Throughout the video, viewers are reminded of the three response actions to take if they encounter an active shooter: run, hide, or fight. This is reinforced through demonstrations of these response actions by the actors in the video and by the narrative voiceover. To date, there is no available research on the effectiveness of this video in preparing individuals for an active-shooter emergency. To assess the experimental conditions, an appropriate instrument was created and administered to participants.

Instrumentation

Before and after viewing an experimental condition, each participant was asked to respond to three measures focusing on their safety self-efficacy, perceived personal campus safety salience, and their safety knowledge. Following the video, the posttest also included items to assess whether participants had any prior experience with a school shooting. Demographic information was requested in the last section of the questionnaire. Correlations of all scales are presented in Table 1.

Safety self-efficacy

To assess safety self-efficacy, we adapted two items from the general self-efficacy scale from Schwarzer and Jerusalem (1995) to focus specifically on campus safety. Partici- pants used a 5-point Likert-type scale (1 = Strongly disagree, 5 = Strongly agree) to respond to the items such as “I am confident in my ability to handle an emergency on campus” and “I feel prepared to manage my safety during an active-shooter emer- gency on campus.” Cronbach’s alpha for the scale of safety self-efficacy in the pretest was .73 (M = 3.14, SD = 0.88). The scale reliability of safety self-efficacy in the posttest was .76 (M = 3.51, SD = 0.75).

Campus safety salience

This scale was created by the researchers for this study based off of items from multiple safety-climate surveys. In the pretest and in the posttest participants used a four-item scale. Items included prompts like “In general, I feel safe as a student at this university” and “I typically don’t think about my safety on campus.” Participants responded using a 5-point Likert type scale (1 = Strongly disagree, 5 = Strongly agree).

446 J. L. Ford & S. S. Frei

Cronbach’s alpha for the scale in the pretest was .70 (M = 3.43, SD = 0.72), and, for the four-item posttest, it was .68 (M = 3.42, SD = 0.68).

Safety knowledge

To determine the participant’s knowledge of appropriate response behaviors in an active-shooter emergency, a test was created based on the information in the video. The researchers created an eight-item quiz that participants took before and after viewing the intervention based directly on information conveyed through the video. There were seven true/false prompts and one multiple-choice question. For instance, some of the true/false statements read: “Even if others insist on staying in the building, you should try and get out” and “Never fight with an active shooter.” A paired- samples t test was calculated to compare the mean pretest score to the mean posttest score. The mean on the pretest was 4.09 (SD = 1.17), and the mean on the posttest was 5.81 (SD = 1.90). A significant increase from the pretest to the posttest was found, t (240) = 12.95, p < .001.

Procedure

Participants were informed about the opportunity to participate in this study through a Web-administered extra-credit system within the Department of Communication Studies at a large Southwestern university in the United States. After accepting the informed consent, participants completed the questions in the pretest. Next, they were randomly assigned to one of the six experimental conditions where they read a message encouraging participation in the training and were subsequently given a link to view the video. Participants made the decision of how long they wanted to watch the 5-minute video, if they chose to watch it at all. Following the posttest, they were asked approximately how many minutes of the video they watched. Finally, they

Table 1 Correlations of Scales

Variable Mean SD 1 2 3 4 5 6 7 8 9

1. Safety Self-Efficacy (Pre) 3.17 0.42

2. Safety Self-Efficacy (Post) 3.10 0.44 .67**

3. Safety Self-Efficacy (Change) −.07 0.35 −.34** .48**

4. Campus Safety Salience (Pre) 3.43 0.72 .12 .15* .04

5. Campus Safety Salience (Post) 3.42 0.68 .10 .14* .05 .78**

6. Campus Safety Salience (Change) −.01 0.47 −.04 −.03 .00 −.41** .25**

7. Knowledge (Pre) 4.10 1.17 .05 .13 .12 −00 .00 .01

8. Knowledge (Post) 5.81 1.90 −.01 −.04 −.02 .07 −.08 −.22** .15*

9. Knowledge (Change) 1.73 2.07 −.03 −.09 −.06 .06 −.09 −.21** −.43** .83**

10. Prior Experience 1.57 0.50 −.01 .02 .04 .10 .09 −.03 .06 −.02 −.06

*p < .05. **p < .001.

Message Characteristics and Protection Motivation 447

completed a posttest that measured changes in the variables of interest, as well as asked for demographic information. Names and personal information were collected only by the extra-credit system. Thus, the participants remained anonymous to the researchers.

Manipulation Check

To find whether the experimental manipulations were effective, a chi-square test of independence was performed. For message medium, participants were asked, “What type of message did you receive when you were told about the safety video?” and selected (a) e-mail, (b) Tweet, or (c) text message. The chi-square indicated that the manipulations for message medium were successful. There was a meaningful difference between participants’ perception of the medium and those who received the message via e-mail, Tweet, and text message, X2 (4) = 252.34, p < .001.

For the message frame, participants were asked to respond to an item that assessed their affective response to the message. The item measuring participant’s affective response to the condition read, “The message I received about the safety video (i.e., e-mail, text, or Tweet) creates a feeling of fear in me.” This item was answered using a 5-point Likert type scale (1 = Strongly disagree, 5 = Strongly agree). Although there was a difference between the means in the fear-based message (M = 3.24, SD = 0.96) and the direct message (M = 3.08, SD = 1.03), the t test did not result in a significant difference, t(236) = −1.28, p = .202.

RESULTS

Research Question 1 asked which combination of message frame (fear-based or direct information) and message medium (e-mail, text, or Tweet) influenced individuals to complete the training video. To answer this research question, we used a 3 x 2 between-subjects factorial analysis of variance (ANOVA) comparing the completion of the training video based on message frame (fear-based or direct information) and message medium (e-mail, text, or Tweet). The main effect for message frame was not significant, F(1, 239) = 0.33, p > .05. The main effect for message medium was significant, F(2, 238) = 3.82, p < .05. Post hoc analysis revealed that those receiving the email (M = 1.56, SD = 0.50) were more likely to complete the video than those in the text-message condition (M = 1.36, SD = 0.48). Further, a significant interaction effect was found, F(5, 235) = 2.76, p < .05. This means that the combination of message frame and message medium influenced the completion of the training video. Specifically, an e-mail with a fear-based frame was more likely to lead to video completion than a Tweet with a fear-based message (Mdn = 0.35, SE = 0.11, p < .05). This was the only significant difference among the experimental conditions and video completion. The effect size for this analysis (r2 = .06) indicated a small-to- medium effect size.

448 J. L. Ford & S. S. Frei

Research Question 2 asked which combination message frame (fear-based or direct information) and message medium (e-mail or Tweet) produced the greatest change in (a) personal campus safety salience, (b) safety knowledge, and (c) safety self-efficacy. To answer this research question, we used a multivariate analysis of covariance (MANCOVA) to examine the combination of fear-based frames and message medium in the outcome measures. In the analysis, we controlled for prior campus safety experience, having watched the video before, and completion of the entire training video. No significant effect was found, λ(12, 426) = 0.94, p > .05. Follow-up univariate analyses of covariance (ANCOVAS) indicated that neither personal campus safety salience, safety knowledge, nor safety self-efficacy were influenced by the combination of fear appeals and media. In other words, there are no significant differences between the outcome measures based on the various message frames presented.

The final research question asked if the single predictor variable of watching the training video changed the three target variables (individuals’ safety salience, knowledge, or safety self-efficacy), while controlling for the three variables (prior campus safety experience, watching the video before the experiment, and the treatment condition). To answer this question, we used three separate simple linear regressions. The first regression was significant, F(4, 230) = 3.86, p < .01, R2 = .06. Thus, completing the training video (β = 1.48, p < .05) was a significant predictor of change in personal campus safety salience. The second regression was signifi- cant, F(4, 233) = 32.96, p < .001, R2 = .36. This indicates that watching the training video (β = 1.34, p < .001) was a significant predictor of change in safety knowledge. The third regression was also significant, F(4, 227) = 2.55, p < .05, R2 = .04. Thus, the training video was a significant predictor of change in safety self-efficacy. This means that individuals who watch the training video increase their knowledge of appropriate active-shooter response behaviors, increase their awareness of safety on campus and feel more proficient in their ability to respond to these events effectively.

DISCUSSION

This experiment extends the literature on safety-training interventions by consider- ing whether the frame and medium of the initial message promoting training participation has a role in training completion. This applied research aids campus safety managers and police personnel tasked with preparing the staff, faculty, and students of U.S. campuses to appropriately respond to an active-shooter emergency. The following offers several practical and theoretical implications based on the findings from this study. In particular, we address how our findings resonate with the extant scholarship on protection motivation, message characteristics, and safety self-efficacy. Toward this end, we begin with a discussion of the practical implications.

Message Characteristics and Protection Motivation 449

Practical Implications

As active-shooter scenarios become more commonplace in campuses and schools across the country, efforts to train responders are increasing (Kingshott & McKenzie, 2013). Through videos like the one used in this study, campus administrators are preparing their members to respond appropriately to these events. This study focuses on the characteristics of messages promoting video-based safety training. Based on our findings, the message frame and medium do not affect an individual’s motivation to protect themselves and others in a campus safety context. The findings indicate that e-mails with fear-based frames compared to fear-based Tweets led more individuals to complete the training video, but that fear-based messages alone are not responsible for increasing personal campus safety salience, safety knowledge, or safety self-efficacy. Consequently, safety practitioners ought to use this information to better disseminate safety messages using a variety of mediums.

In addition to the message frame and medium, we were also interested in how the training video affected various outcomes related to protection motivation—personal campus safety salience, safety knowledge, and safety self-efficacy. We found that the video led to a positive change in all three of these outcomes. This is encouraging information for administrators considering using Run, Hide, Fight as an active- shooter response-training video. Regardless of the message used to promote the video, it appears that when students completed the video, they became more knowl- edgeable of what to do in emergency situations, felt more confident in their abilities to respond and became more aware of safety on campus. Taken as a whole, these findings carry enormous implications for campuses tasked with the responsibility of preparing organizational members for these events. Giving active-shooter response training videos more widespread attention could help better prepare schools for these unthinkable events. In fact, campuses ought to consider ways to make viewing these videos mandatory (e.g., during student orientation, employee training, or on the first day of class) considering the improved safety knowledge, efficacy, and awareness of safety on campus. Beyond offering practical implications for individuals tasked with managing campus safety, the present study encourages scholars interested in safety- training initiatives to consider the utility of protection motivation theory.

Theoretical Implications

Protection motivation theory posits that individuals must deal with the noxious feelings fear causes by either responding effectively or ineffectively (Rogers, 1975). This decision is mediated by an individual’s cognitive assessment of the threat and their ability to effectively handle the situation (see Figure 1). Despite using PMT to guide our experiment, the results did not consistently support this model. Whereas PMT advances the idea that fear-based frames will have the most impact on partici- pants’ completion of this training video, this was only true for fear-based messages sent via e-mail when compared to fear-based messages sent via text or Twitter. Yet, when each fear-based message medium was assessed individually, no single medium

450 J. L. Ford & S. S. Frei

led to a significant effect on the completion of the safety-training video. Considering the message medium alone, this study supports the use of e-mail messages over text messages to encourage individuals to watch a training video on active-shooter responses. Though previous research indicates that Twitter is an effective medium for sending emergency messages (Crowe, 2011), this study does not replicate the usefulness of this medium. In fact, there was no significant difference between this medium and the two other media tested on video completion.

In light of the discrepancies between the study’s findings and PMT, we offer several explanations. First, it is conceivable that any message referencing a potential school shooting, regardless of the type of frame, will induce fear. Thus, including a fear-based frame on messages encouraging participation in active-shooter response training is redundant. Bearing in mind that the prevalence of school shootings has produced a heighted sense of fear among college students (Kaminski et al., 2010), it may be difficult to divorce the effects of fear-based messages from the fear induced by the thought of such events.

Second, the results of this study expose a problem with the midpoint of Rogers’ (1975) model when used in this context. The original model suggests that message characteristics should have led participants to a more heightened assessment of their personal campus safety salience. Yet, there was a nonsignificant relationship between these variables. A closer look at the cognitive mediating variables in this model reveals that personal safety salience is significantly related to perceived safety self-efficacy. Accordingly, individuals who are actively concerned about their safety on campus feel more confident in their ability to manage potential safety situations. Surprisingly, an individual’s prior experience with a campus emergency does not produce higher safety self-efficacy. Perhaps facing the uncertainty of a similar crisis does not make one feel more prepared for another campus emergency. Future research, especially studies guided by PMT, should investigate the relationship between prior experience and self- efficacy.

Limitations

This experiment was designed to capture whether the nuances of message character- istics affect individuals’ protection motivation. Despite the intent of the experiment, we recognize that there are inherent limitations to its design. First, the nonsignificant manipulation check for fear-based messages limits our ability to draw conclusions from these conditions. Seeing as the results reported in this study are from the second attempt at data collection because of a previous ineffective manipulation check, it is evident that there is an inability to effectively manipulate fear-based messages around the topic of school shootings. Thus, messages about school shootings may produce fear regardless of the message frame. Second, the sample in this study was over- whelmingly female, which was also seen in the previous data collection. Perhaps females are more concerned about their safety on campus than males, leading them to participate in this safety study. This is an area ripe for future research.

Message Characteristics and Protection Motivation 451

Third, the data were collected from a single institution that has experienced an active shooter within the past 4 years. This may have influenced some of the results and skewed perceptions of safety self-efficacy and personal campus safety salience. It is important to consider such broad environmental factors when replicating this experiment in future studies.

Future Directions

To better understand how to train the staff, faculty, and students at our nation’s schools to respond to active-shooter emergencies, future research should consider how an individual’s perceptions of organizational preparedness affects protection motiva- tion. In other words, when schools make observable efforts to prepare and equip their members for a potential school shooting, does this diminish the safety information- seeking efforts of individuals? Additionally, considering the pervasiveness of message overload within our personal and organizational lives, future research should continue to investigate the effects of message overload on an individual’s attention to safety- related information (Stephens, Barrett, & Mahometa, 2013). If message overload limits our attention to these messages, it is imperative to investigate ways to reach these individuals with this potentially life-saving information.

Another area for future research is to assess participants’ motivation for training as a possible control in this experiment. Motivation for training has been studied extensively in organizational settings, though often within corporations and nonprofit organizations (Beier & Kanfer, 2010). Research indicates that there is a relationship between self-efficacy and motivation for training (Lim & Morris, 2006), leading us to reason that safety self-efficacy in this experiment may be moderated by an individual’s motivation to learn. Taken together, a further examination of the relationship between self-efficacy, motivation to learn, and the motivation to share information learned with others has serious implications for campus safety officials.

The impetus for creating safer, more active-shooter-prepared schools has never been greater. This study represents an effort toward producing safer schools by expanding our understanding of protection motivation theory to a new context. In addition, this research broadens future use of this theory by incorporating the relationship between message characteristics and subsequent protection motivation actions. The evidence in this study provides a compelling argument for shifting our previous ways of conceptua- lizing fear-based frames as a material characteristic to an event-based characteristic. The context of a school shooting may already produce enough fear to influence individuals to prepare for these unthinkable events. The current study demonstrates the value in exploring how more granular factors, like message characteristics and personal campus safety salience, influence the completion of these training initiatives.

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Article

The Mental Health Consequences of Mass Shootings

Sarah R. Lowe1 and Sandro Galea2

Abstract Mass shooting episodes have increased over recent decades and received substantial media coverage. Despite the potentially widespread and increasing mental health impact of mass shootings, no efforts to our knowledge have been made to review the empirical literature on this topic. We identified 49 peer-reviewed articles, comprised of 27 independent samples in the aftermath of 15 mass shooting incidents. Based on our review, we concluded that mass shootings are associated with a variety of adverse psychological outcomes in survivors and members of affected communities. Less is known about the psychological effects of mass shootings on indirectly exposed populations; however, there is evidence that such events lead to at least short-term increases in fears and declines in perceived safety. A variety of risk factors for adverse psychological outcomes have been identified, including demographic and pre-incident characteristics (e.g., female gender and pre-incident psychological symptoms), event exposure (e.g., greater proximity to the attack and acquaintance with the deceased), and fewer psychosocial resources (e.g., emotion regulation difficulties and lower social support). Further research that draws on pre-incident and longitudinal data will yield important insights into the processes that exacerbate or sustain post-incident psychological symptoms over time and provide important information for crisis preparedness and post-incident mental health interventions.

Keywords mass shootings, school shootings, mass trauma, posttraumatic stress, major depression, psychosocial resources, risk and protective factors

Over the past few decades, mass shooting episodes—defined

as events involving one or more persons attempting to kill

multiple people, and at least one unrelated person, in an area

occupied by multiple unrelated persons (Blair & Martaindale,

2013)—have received substantial media coverage and captured

public attention. Recent investigations have suggested that mass

shooting episodes are becoming more frequent. For example, a

report by researchers at the Texas State University identified

84 episodes in the United States between 2000 and 2010 and

noted a trend toward increasing frequency of time (Blair &

Martaindale, 2013). An investigation by the Mother Jones

news organization, using a slightly different definition of mass

shootings (events that were ‘‘senseless, random, or at least public

in nature’’), identified 70 episodes occurring between 1982 and

2012 and noted a recent surge in these events, with nearly half

occurring since 2006.

In addition to the increasing frequency of mass shootings

episodes, key events over the past decade have had unusually

large numbers of fatalities and injuries—for example, 33 fatal-

ities and 23 injuries in the 2007 Virginia Tech massacre, 12

fatalities and 58 injuries in the 2012 Aurora, Colorado theater

shooting, and 28 fatalities and 2 injuries in the Sandy Hook ele-

mentary school shooting in Newtown, Connecticut (Follman,

Aronsen, & Pan, 2014). In an epidemiological review of school

shootings, Shultz, Cohen, Muschert, and Flores de Apodaca,

(2013) noted that just three events (Columbine, Sandy Hook,

and Virginia Tech) accounted for over half of the fatalities in

the 215 incidents between 1990 and 2012.

Research indicates that exposure to assaultive violence, or

learning that a close friend or loved one has faced such expo-

sure, is associated with an increased incidence of a range of

negative mental health outcomes, among them posttraumatic

stress disorder (PTSD) and major depression (MD; e.g.,

Breslau et al., 1996; Lowe, Blachman-Forshay, & Koenen,

2015). It is therefore likely that mass shootings exert a psycho-

logical toll on their direct victims and members of the commu-

nities in which they took place. Moreover, media coverage of

mass shootings and their aftermath reaches far beyond affected

communities to the entire nation and beyond. As shown in the

1 Department of Epidemiology, Columbia University, Mailman School of Public

Health, New York, NY, USA 2 Department of Epidemiology, Boston University School of Public Health,

Boston, MA, USA

Corresponding Author:

Sarah R. Lowe, Department of Epidemiology, Columbia University, Mailman

School of Public Health, 722 West 168th Street, Room 720-F, New York, NY

10032, USA.

Email: [email protected]

TRAUMA, VIOLENCE, & ABUSE 2017, Vol. 18(1) 62-82 ª The Author(s) 2015 Reprints and permission: sagepub.com/journalsPermissions.nav DOI: 10.1177/1524838015591572 journals.sagepub.com/home/tva

aftermath of the September 11 terrorist attacks (9/11), such

indirect exposure can have mental health consequences (Hen-

ricksen, Bolton, & Sareen, 2010). For example, in the National

Epidemiologic Survey of Alcohol and Related Conditions,

indirect exposure to 9/11 through the media was associated

with increased risk for mood, anxiety and substance use disor-

ders, and PTSD, relative to no reported 9/11 exposure (Hen-

ricksen et al., 2010).

Despite the potentially widespread and increasing mental

health impact of mass shooting episodes, no efforts to our

knowledge have been made to synthesize the extant literature

on this topic. In this article, we therefore aim to conduct a

review of empirical investigations on the mental health conse-

quences of mass shootings. We provide an overview of this

body of research, including the prevalence and predictors of

various mental health outcomes. Based on this review, we

make recommendations for future research and post-incident

interventions.

Method

We conducted a literature search in PsycInfo and PubMed data-

bases, using both general terms (e.g., shooting, tragedy), and

names of specific events (e.g., Columbine, Sandy Hook) com-

piled from comprehensive lists of mass shootings (Follman,

Aronsen, Pan, & Caldwell, 2013; Henriques, 2013; Shultz

et al., 2013). In our review, we used the aforementioned defini-

tion of mass shootings: events involving one or more persons

attempting to kill multiple people, and at least one unrelated

person, in an area occupied by multiple unrelated persons

(Blair & Martaindale, 2013). We included events that took

place in any country in the world. We limited our search to arti-

cles in peer-reviewed, English language journals that included

quantitative indices of post-event mental health, including

symptoms of psychiatric disorders (e.g., PTSD and MD) and

general symptoms that cut across disorders (e.g., psychological

distress and fear). We therefore excluded qualitative studies,

and quantitative studies that focused solely on other outcomes

(e.g., perceptions of social solidarity and coping strategies). In

addition to studies identified through database searches, refer-

ence lists of articles on this topic were reviewed to identify

additional studies.

The coding processes consisted of two main steps. First, we

coded for study characteristics. We recorded the mass shooting

event that was the focus of each study, including the year, loca-

tion, context, demographic characteristics of the perpetrator, and

numbers of injuries and fatalities during the incident, and

whether the study focused on more than one event. We noted

instances in which data from the same sample were used across

different analyses to determine how many independent samples

were there across the studies. In addition, we noted whether the

sample was affected (defined as direct victims of the shooting or

members of the community in which the shooting took place) or

remote (defined as consisting primarily of members outside of

the affected community, e.g., national samples or students at a

university in a difficult region), basic characteristics of the

sample (e.g., whether participants were students or emergency

personnel), sample sizes, and timing of assessments.

Second, we coded the prevalence estimates and predictors of

mental health outcomes in each study. We recorded the mental

health outcomes assessed, the measures and diagnostic classifi-

cation systems used, and the prevalence of psychiatric disor-

ders. We then listed significant predictors of mental health

outcomes and, in doing so, specified the mental outcome

included in the analysis (e.g., diagnosis or symptom severity

score, change in symptoms over time) and timing of assess-

ment. Finally, we noted results that went beyond prevalence

estimates and predictors, such as those focused on mechanisms

leading to mental health outcomes.

Both authors formulated the article selection process, inclu-

sion criteria, and coding scheme. The first author conducted the

literature search, coded selected articles, and checked and

rechecked coding for accuracy, and the second author oversaw

the review process and provided regular feedback.

Study Characteristics

We identified a total of 49 studies on 15 different mass shoot-

ing incidents that took place from 1984 to 2008. Three of the

studies focused on two different events combined. Table 1 pro-

vides basic information on each event (e.g., location, number of

injuries, and fatalities) in chronological order. Thirteen events

took place in the United States, and two took place in Finland.

The majority of events (n ¼ 9) were in a secondary school or university context, whereas the remainder took place in other

locations (e.g., local businesses). In total, there were 27 inde-

pendent samples (three from studies focusing on two different

events combined). Of the 27 independent samples, 22 were

classified as affected samples and 5 as remote samples (two

affected and one remote from the studies focusing on two dif-

ferent events combined).

Post-Shooting Mental Health Outcomes

Table 2 denotes the mental health outcomes included in each

study, as well as the measures used to assess them and the clas-

sification system used to determine prevalence estimates if this

information was available.

Psychiatric Disorders and Prevalence Estimates

PTSD. Posttraumatic stress symptoms (PTSS) were reported in the majority of studies—36 studies from 18 independent sam-

ples. Eighteen of these studies (from 14 independent samples)

included a prevalence estimate of PTSD. The lowest PTSD pre-

valence reported was 3% among parents of children exposed to an elementary school shooting 6–14 months post-incident,

determined using conservative Diagnostic and Statistical Man-

ual of Mental Disorders, Third Edition, Revised (DSM-III-R)

criteria with the PTSD–Reaction Index (PTSD-RI; Schwarz

& Kowalski, 1991a). The highest prevalence reported was

91% among children in the same study, using liberal

Lowe and Galea 63

(proposed) DSM-IV criteria and the children’s version of the

PTSD-RI (Schwarz & Kowalski, 1991b).

Major depression. The second most commonly assessed psychia- tric disorder was MD. MD symptoms were assessed in 16 stud-

ies using 10 independent samples, and the prevalence of MD

was estimated in 8 studies using 7 independent samples. The

lowest prevalence of MD was 4.9% among survivors of the 1991 cafeteria shooting in Killeen, TX, assessed 1 year after

the event using the Diagnostic Interview Schedule for DSM-

III-R (North, Smith, & Spitznagel, 1997). The highest preva-

lence was 71%, detected in a combined sample of Virginia Tech and Northern Illinois University (NIU) students 2 weeks

after the attacks at their respective campuses, assessed using

the Center for Epidemiologic Studies Short Depression Scale

(Vicary & Fraley, 2010).

Other psychiatric disorders. In addition to PTSD and MD, preva- lence estimates were provided for the following psychiatric dis-

orders: generalized anxiety disorder (GAD; three studies and

three independent samples): range: 0.0–0.9%; acute stress disor- der (one study): 33%; alcohol-related conditions (e.g., alcohol abuse, alcohol dependence, alcoholism; four studies, four inde-

pendent samples) range: 0–9%; drug use disorder (one study): range: 0–0.7%; panic disorder (two studies and two independent samples) range: 1–2.4%; adjustment disorder (one study): 9.1%; social phobia (one study): 3%; and antisocial personality

disorder (one study): 0–0.8% (Classen, Koopman, Hales, & Spiegel, 1998; Johnson, North, & Smith, 2002; North, Smith,

McCool, & McShea, 1989; North et al., 1997; Séguin et al.,

2013; Trappler & Friednman, 1996).

Comparing Prevalence Estimates

There are at least four issues to consider when comparing the

prevalence estimates of mental health outcomes across the

studies in our review. First, variation in sample characteristics

that, as discussed in more detail later, could influence post-

event mental health, including variation in demographic char-

acteristics and exposure to the incident. Second, there is wide

variation in the timing of assessments, spanning from approx-

imately 1 week to 32 months post-incident. As shown in studies

with multiple waves (e.g., Nader, Pynoos, Fairbanks, & Freder-

ick, 1990; North et al., 1997), the prevalence of psychiatric dis-

orders tends to decrease over time, limiting the extent to which

estimates at varying time points after different events can be

compared. Third, different measures and diagnostic criteria

were used across the studies, which could certainly affect pre-

valence rates. The influence of diagnostic criteria on preva-

lence rates was most clearly demonstrated in the aftermath of

the 1988 elementary school shooting, wherein the prevalence

of PTSD among child survivors at 6–14 months post-incident

ranged from 8% to 91% and among their parents from 3% to 54% using conservative DSM-III-R criteria and liberal

Table 1. Summary of Mass Shooting Incidents and Characteristics of Peer-Reviewed Studies.

Year Location Context Perpetrator Fatalities Injuries

Peer- Reviewed Articles

Samples (Affected, Remote)

1984 Los Angeles, CA Elementary school Adult African American male

3 14 2 1 (1, 0)

1984 San Ysidro, CA Fast food restaurant Adult White male 21 15 1 1 (1, 0) 1987 Russellville, AR Four local businesses Adult White male 2 4 1 1 (1, 0) 1988 Winnetka, IL Elementary school Adult White female 2 5 6 3 (3, 0) 1991 Killeen, TX Cafeteria-style restaurant Adult White male 24 20 5 2 (2, 0) 1992 St. Louis, MO Courthouse Adult White male 1 5 1 1 (1, 0) 1993 San Francisco, CA Office building Adult White male 6 14 1 1 (1, 0) 1994 Brooklyn, NY Brooklyn Bridge Adult Lebanese-born

immigrant male 1 3 1 1 (1, 0)

1999 Columbine, CO High school Two adolescent White males

15 21 3 3 (0, 3)

2006 Montreal, Quebec, Canada

University (Dawson College) Adult Indo-Canadian male

2 17 1 1 (1, 0)

2007 Tuusula, Finland High school (Jokela High School) Adolescent White male 9 19 3 1 (1, 0) 2007 Blacksburg, VA University (Virginia Polytechnic Institute

and State University) Adult South Korean

male 33 25 11 4 (3, 1)

2008 DeKalb, IL University (Northern Illinois University) Adult White male 6 18 8 2 (2, 0) 2008 Conway, AR University (University of Central

Arkansas) Four adult African

American males 2 1 1 1 (1, 0)

2008 Kauhajoki, Finland University (Seinäjoki University of Applied Sciences)

Adult White male 11 1 1 1 (1, 0)

Note. Affected samples included participants who lived in the communities in which the incident occurred; participants did not have to be directly exposed to the event. Remote samples included members of other communities and nationally representative samples. Table does not include three studies that each focused on two different events (two affected samples, one remote sample).

64 TRAUMA, VIOLENCE, & ABUSE 18(1)

T a b

le 2 .

S u m

m ar

y o f th

e F in

d in

gs F ro

m P e e r-

R e vi

e w

e d

S tu

d ie

s o n

th e

P sy

ch o lo

gi ca

l E ff e ct

s o f M

as s

S h o o ti n g

In ci

d e n ts

.

A u th

o r

(Y e ar

) N

S am

p le

T im

in g

M e n ta

l H

e al

th O

u tc

o m

e s

(M e as

u re

; C

la ss

if ic

at io

n S ys

te m

) P re

va le

n ce

P re

d ic

to rs

1 9 8 4 —

E le

m e n ta

ry sc

h o o l in

L o s

A n ge

le s,

C A

(1 a)

P yn

o o s

e t

al .

(1 9 8 7 )

1 5 9

E le

m e n ta

ry sc

h o o l st

u d e n ts

(a ff ec

te d )

1 m

o n th

P T

S D

(P T

S D

-R I,

D S M

-I II )

P T

S D

: 6 0 .4

% P T

S S ,1

m o n th

:P ro

x im

it y

to at

ta ck

,g re

at e r

ac q u ai

n ta

n ce

w it h

th e

d e ce

as e d

vi ct

im (1

b )

N ad

e r,

P yn

o o s,

F ai

rb an

k s,

an d

F re

d e ri

ck (1

9 9 0 )

1 0 0

a 1

m o n th

, 1 4

m o n th

s P T

S D

(P T

S D

-R I,

D S M

-I II );

G ri

e f (b

ri e f in

ve n to

ry )

— P T

S S , 1 4

m o n th

s: P ro

x im

it y

to at

ta ck

, gr

e at

e r

ac q u ai

n ta

n ce

w it h

th e

d e ce

as e d

vi ct

im ; G

ri e f:

gr e at

e r

ac q u ai

n ta

n ce

w it h

th e

d e ce

as e d

1 9 8 4 —

F as

t- fo

o d

re st

au ra

n t

in S an

Y si

d ro

, C

A (1

) H

o u gh

e t

al .

(1 9 9 0 )

3 0 3

M id

d le

-a ge

d M

e x ic

an A

m e ri

ca n

w o m

e n

fr o m

th e

co m

m u n it y,

b u t

w h o

w e re

n o t

d ir

e ct

ly in

vo lv

e d

in th

e in

ci d e n t

(a ff ec

te d )

6 – 9

m o n th

s P T

S D

(s ca

le d e ri

ve d

fo r

th e

st u d y,

b as

e d

o n

th e

D IS

; D

S M

-I II );

M D

(C E S -D

)

P T

S D

, p o st

-i n ci

d e n t:

1 2 .6

% ;

P T

S D

, p as

t- m

o n th

: 6 .8

% S e ve

re P T

S D

(s ig

n ifi

ca n ce

of tr

en d s n ot

te st

ed ):

w id

o w

e d , se

p ar

at e d

o r

d iv

o rc

e d

st at

u s,

o ld

e r

ag e , n o

ch ild

re n

at h o m

e , lo

w e r

in co

m e , u n e m

p lo

ym e n t,

h av

in g

fr ie

n d s/

re la

ti ve

s in

vo lv

e d

in e ve

n t,

fa ir

– p o o r

p h ys

ic al

h e al

th , h ig

h e r

M D

sy m

p to

m s.

M ild

P T

S D

(s ig

n ifi

ca n ce

of tr

en d s n ot

te st

ed ):

m id

d le

-a ge

,h av

in g

th re

e o r

m o re

ch ild

re n

at h o m

e , m

id d le

in co

m e , h av

in g

fr ie

n d s/

re la

ti ve

s in

vo lv

e d

in th

e e ve

n t,

fa ir

– p o o r

p h ys

ic al

h e al

th

1 9 8 7 —

F o u r

lo ca

l b u si

n e ss

e s

in R

u ss

e llv

ill e , A

R (1

) N

o rt

h , S m

it h ,

M cC

o o l,

an d

S h e a

(1 9 8 9 )

1 8

E m

p lo

ye e s

at tw

o o f th

e fo

u r

lo ca

l b u si

n e ss

e s

w h o

w e re

e it h e r

at w

o rk

d u ri

n g

th e

sh o o ti n g

(n ¼

1 5 ) o r

ab se

n t

(n ¼

1 1 ; a ff ec

te d )

4 – 6

w e e k s

P T

S D

, M

D , G

A D

, A

lc o h o lis

m (D

IS /D

is as

te r

S u p p le

m e n t,

D S M

-I II )

P T

S D

: 5 .6

% ; M

D : 1 6 .7

% ;

G A

D : 0 .0

% ; A

lc o h o lis

m :

0 .0

%

—

1 9 8 8 —

E le

m e n ta

ry sc

h o o l in

W in

n e tk

a, IL

(1 a)

S ch

w ar

z an

d K

o w

al sk

i (1

9 9 1 a)

1 3 0

E le

m e n ta

ry sc

h o o l st

u d e n ts

(n ¼

6 4 )

an d

th e ir

p ar

e n ts

(n ¼

6 6 ; a ff ec

te d )

6 – 1 4

m o n th

s P T

S D

(P T

S D

-R I,

D S M

-I II -R

, lib

e ra

l m

o d e ra

te an

d co

n se

rv at

iv e

cr it e ri

a)

P T

S D

, ch

ild re

n , D

S M

-I II -R

: 5 0 %

, (l ib

e ra

l) , 4 1 %

(m o d e ra

te ),

8 %

(c o n se

rv at

iv e );

P T

S D

, p ar

e n ts

, D

S M

-I II -R

, p ro

p o se

d : 3 9 %

(l ib

e ra

l) ,

2 4 %

(m o d e ra

te ),

3 %

(c o n se

rv at

iv e )

P T

S D

, ch

ild re

n (p

re d ic

to rs

o f d ia

gn o si s

b a se

d o n

lib er

a l,

m o d er

a te

, o r

co n se

rv a ti ve

cr it er

ia ):

p e rc

e p ti o n

th at

h e

o r

sh e

w o u ld

ge t

sh o t

o r

w as

in d an

ge r

d u ri

n g

e ve

n t,

in cr

e as

e d

p h ys

ic al

sy m

p to

m s,

in cr

e as

e d

vi si

ts to

sc h o o l n u rs

e , in

cr e as

e d

o r

n e w

fe ar

s, gu

ilt . P T

S D

, p ar

e n ts

(p re

d ic

to rs

o f

d ia

gn o si s

b a se

d o n

lib er

a l,

m o d er

a te

, o r

co n se

rv a ti ve

cr it er

ia ):

fe lt

n u m

b ,s

ca re

d ,o

r fe

ar fu

l th

at th

e al

le ge

d p e rp

e tr

at o r

w as

st ill

o n

th e

lo o se

(c o n ti n u ed

)

65

T a b

le 2 .

(c o n ti n u e d )

A u th

o r

(Y e ar

) N

S am

p le

T im

in g

M e n ta

l H

e al

th O

u tc

o m

e s

(M e as

u re

; C

la ss

if ic

at io

n S ys

te m

) P re

va le

n ce

P re

d ic

to rs

(1 b )

S ch

w ar

z an

d K

o w

al sk

i (1

9 9 1 b )

1 3 0

a 6 – 1 4

m o n th

s P T

S D

(P T

S D

-R I;

D S M

-I II ,

D S M

-I II -R

[s am

e p re

va le

n ce

s as

S ch

w ar

z &

K o w

al sk

i, 1 9 9 1 a]

, p ro

p o se

d D

S M

-I V

, lib

e ra

l, m

o d e ra

te , an

d co

n se

rv at

iv e

cr it e ri

a)

P T

S D

, ch

ild re

n , D

S M

-I II ,

p ro

p o se

d D

S M

-I V

: 9 1 %

, 4 1 %

(l ib

e ra

l) , 6 1 %

, 4 1 %

(m o d e ra

te ),

1 6 %

, 9 %

(c o n se

rv at

iv e );

P T

S D

, p ar

e n ts

, D

S M

-I II , p ro

p o se

d D

S M

-I V

: 5 2 %

, 5 4 %

(l ib

e ra

l) ,

1 6 %

, 2 4 %

(m o d e ra

te ),

4 %

, 6 %

(c o n se

rv at

iv e )

—

(2 a)

S ch

w ar

z an

d K

o w

al sk

i (1

9 9 2 a)

2 4

S ch

o o l p e rs

o n n e l (a

ff ec

te d )

6 m

o n th

s P T

S D

(P T

S D

-R I;

D S M

-I II )

— P T

S S : p e rs

o n al

it y

tr ai

ts —

gu ilt

an d

re se

n tm

e n t,

in se

cu ri

ty , an

d p sy

ch as

th e n ia

(2 b )

S ch

w ar

z an

d K

o w

al sk

i (1

9 9 2 b )

2 4

S u b sa

m p le

co m

p le

te d

2 w

av e s

(n ¼

1 3 ; a ff ec

te d )a

6 m

o n th

s, 1 8

m o n th

s P T

S D

(P T

S D

-R I;

D S M

-I II );

M D

(B D

I) ; G

A D

(S T

A I)

— P T

S S , 6

m o n th

s: lo

ss to

fo llo

w -u

p

(2 c)

S ch

w ar

z, K

o w

al sk

i, an

d M

cN al

ly (1

9 9 3 )

2 4

S u b sa

m p le

co m

p le

te d

2 w

av e s

(n ¼

1 2 ; a ff ec

te d )a

6 m

o n th

s, 1 8

m o n th

s P T

S D

(P T

S D

-R I;

D S M

-I II );

M D

(B D

I) ; G

A D

(S T

A I)

— P T

S S , 6

m o n th

s: e n la

rg e m

e n t

o f re

ca ll

o f

e m

o ti o n al

e x p e ri

e n ce

s (h

yp e ra

ro u sa

l) ,

lif e

th re

at e x p e ri

e n ce

s (h

yp e ra

ro u sa

l) ,

an d

se n so

ry e x p e ri

e n ce

s (a

vo id

an ce

, h yp

e ra

ro u sa

l, to

ta l P T

S S ),

la ck

o f

d im

in is

h m

e n t

in re

ca ll

o f e m

o ti o n al

e x p e ri

e n ce

s (i n tr

u si

o n );

P T

S S , 1 8

m o n th

s: e n la

rg e m

e n t

in re

ca ll

o f se

n so

ry e x p e ri

e n ce

s (h

yp e ra

ro u sa

l) ; M

D sy

m p to

m s,

1 8

m o n th

s: la

ck o f

d im

in is

h m

e n t

in re

ca ll,

p e rc

e iv

e d

ab ili

ty to

h an

d le

st re

ss ;G

A D

sy m

p to

m s:

la ck

o f

d im

in is

h m

e n t

in re

ca ll

o f e m

o ti o n al

e x p e ri

e n ce

s (3

) S lo

an ,

R o ze

n sk

y, K

ap la

n ,

an d

S an

d e rs

(1 9 9 4 )

1 4 0

E m

e rg

e n cy

re sp

o n d e rs

(a ff ec

te d )

6 m

o n th

s P T

S D

(I E S

In tr

u si

o n

an d

A vo

id an

ce )

— P T

S S :f

iv e

in d ic

at o rs

o f jo

b st

re ss

d u ri

n g

th e

e ve

n t—

e x p o su

re to

tr au

m at

ic st

im u li,

ad ve

rs e

w o rk

e n vi

ro n m

e n t,

ti m

e p re

ss u re

, q u an

ti ta

ti ve

w o rk

lo ad

, an

d q u al

it at

iv e

w o rk

lo ad

(i n tr

u si

o n

an d

av o id

an ce

)

1 9 9 1 —

C af

e te

ri a-

st yl

e re

st au

ra n t

in K

ill e e n , T

X (1

a) N

o rt

h , S m

it h ,

an d

S p it zn

ag e l

(1 9 9 4 )

1 3 6

S u rv

iv o rs

(e .g

., re

st au

ra n t

p at

ro n s

an d

e m

p lo

ye e s,

e m

e rg

e n cy

re sp

o n d e rs

; a ff ec

te d )

1 – 2

m o n th

s P T

S D

, M

D , P D

, G

A D

, A

A /

A D

, D

A /D

D , A

S P D

(D IS

; D

S M

-I II -R

)

A t

1 – 2

m o n th

s— P T

S D

: 2 8 .6

% P T

S D

, 1 – 2

m o n th

s: fe

m al

e ge

n d e r,

p re

- in

ci d e n t

M D

(a m

o n g

fe m

al e

p ar

ti ci

p an

ts o n ly

), an

y p re

-i n ci

d e n t

p sy

ch ia

tr ic

d ia

gn o si

s (a

m o n g

fe m

al e

p ar

ti ci

p an

ts o n ly

), p o st

-i n ci

d e n t

M D

, an

y p o st

- in

ci d e n t

p sy

ch ia

tr ic

d is

o rd

e r

(a m

o n g

fe m

al e

p ar

ti ci

p an

ts o n ly

), se

e in

g a

d o ct

o r

o r

co u n se

lo r,

ta k in

g m

e d ic

at io

n (c o n ti n u ed

)

66

T a b

le 2 .

(c o n ti n u e d )

A u th

o r

(Y e ar

) N

S am

p le

T im

in g

M e n ta

l H

e al

th O

u tc

o m

e s

(M e as

u re

; C

la ss

if ic

at io

n S ys

te m

) P re

va le

n ce

P re

d ic

to rs

(1 b )

N o rt

h , S m

it h ,

an d

S p it zn

ag e l

(1 9 9 7 )

1 2 4

a 1 – 2

m o n th

s, 1

ye ar

P T

S D

, M

D , P D

, G

A D

, A

A /

A D

, D

A /D

D , A

S P D

(D IS

; D

S M

-I II -R

)

A t

1 – 2

m o n th

s— M

D : 1 0 .3

% ,

P D

: 2 .3

% , G

A D

: 0 .7

% , A

A /

A D

: 7 .5

% , D

A /D

D : 0 .0

% ,

A S P D

: 0 .0

% ; A

t 1

ye ar

— P T

S D

: 1 7 .7

% , M

D : 4 .9

% ,

P D

: 2 .4

% , G

A D

: 0 .9

% , A

A /

A D

: 5 .7

% , D

A /D

D : 0 .8

% ,

A S P D

: 0 .7

%

P T

S D

, e it

h e r/

b o th

1 – 2

m o n th

s an

d 1

ye ar

: fe

m al

e ge

n d e r,

an y

p re

-i n ci

d e n t

p sy

c h ia

tr ic

d ia

g n o

si s

(a m

o n g

fe m

al e

p a rt

ic ip

an ts

o n ly

), an

y o th

e r

p o

st -

in c id

e n t

p sy

c h ia

tr ic

d is

o rd

e r,

an y

o th

e r

li fe

ti m

e p sy

c h ia

tr ic

d is

o rd

e r,

p re

- in

c id

e n t

M D

, M

D at

1 – 2

m o n th

s, li fe

ti m

e M

D (1

c) N

o rt

h ,

S p it zn

ag e l,

an d

S m

it h

(2 0 0 1 )

1 3 6

a 1 – 2

m o n th

s, 1

ye ar

, 3

ye ar

s P T

S D

, M

D , P D

, G

A D

, A

A /

A D

, D

A /D

D , A

S P D

(D IS

; D

S M

-I II -R

)

— P T

S D

, 1 – 2

m o

n th

s: lo

w e r

ac ti

v e

o u tr

e ac

h an

d in

fo rm

e d

p ra

g m

at is

m co

p in

g at

1 – 2

m o n th

s; P T

S D

, 1

ye ar

: lo

w e r

in fo

rm e d

p ra

g m

a ti

sm co

p in

g at

1 – 2

m o n th

s; P T

S D

, 3

ye ar

s: lo

w e r

in fo

rm e d

p ra

g m

at is

m co

p in

g at

1 – 2

m o n th

s; M

D ,

1 – 2

m o

n th

s: lo

w e r

in fo

rm e d

p ra

g m

at is

m co

p in

g at

1 – 2

m o n th

s; M

D ,

3 ye

ar s:

lo w

e r

ac ti

ve o u tr

e ac

h co

p in

g at

1 – 2

m o

n th

s; A

n y

d is

o rd

e r,

1 – 2

m o

n th

s: lo

w e r

ac ti

ve o u tr

e ac

h an

d in

fo rm

e d

p ra

g m

at is

m co

p in

g at

1 – 2

m o

n th

s; A

n y

d is

o rd

e r,

1 ye

ar :

lo w

e r

in fo

rm e d

p ra

g m

at is

m co

p in

g at

1 – 2

m o

n th

s; A

n y

d is

o rd

e r,

3 ye

ar s:

lo w

e r

in fo

rm e d

p ra

g m

at is

m an

d re

c o n ci

li at

io n

ac c e p ta

n c e

co p in

g at

1 – 2

m o n th

s (1

d )

N o rt

h ,

M cC

u tc

h e o n ,

S p it zn

ag e l,

an d

S m

it h

(2 0 0 2 )

1 1 6

a 1 – 2

m o n th

s, 1

ye ar

, 3

ye ar

s P T

S D

, M

D , P D

, G

A D

, A

A /

A D

, D

A /D

D , A

S P D

(D IS

; D

S M

-I II -R

)

A t

3 ye

ar s—

P T

S D

: 1 8 %

, M

D : 1 0 %

N o

n re

c o

v e ry

fr o

m P T

S D

, 3

y e ar

s: fu

n c ti

o n a l

in te

rf e re

n c e

d u e

to sy

m p to

m s,

h a v in

g se

e n

a m

e n ta

l h e a lt

h p ro

fe ss

io n a l

a t

1 – 2

m o

n th

s; n o

n re

c o

v e ry

fr o

m M

D ,

3 y e a rs

: fa

m il y

h is

to ry

o f

d e p re

ss io

n ,

p ar

e n ta

l h is

to ry

o f

tr e a tm

e n t

fo r

d ri

n k in

g p ro

b le

m s

(2 )

S e w

e ll

(1 9 9 6 )

9 2

P e rs

o n s

e it

h e r

d ir

e c tl

y e x p o

se d

(e .g

., re

st a u ra

n t

p a tr

o n s)

o r

in d ir

e c tl

y e x p o

se d

(e .g

., re

la ti

v e s

o f

d ir

e c tl

y e x p o

se d ;

a ff

e ct

e d )

1 w

e e k , 3

m o n th

s P T

S D

(m o d u le

fr o m

th e

P D

I, D

S M

-I V

) P T

S D

, 1

w e e k : 3 8 .7

% P T

S D

, 1

w e e k : P re

-i n ci

d e n t

P T

S D

; P T

S D

n o n re

co ve

ry , 3

m o n th

s: L o w

e r

tr au

m a-

re la

te d

co n st

ru ct

e la

b o ra

ti o n

(c o n ti n u ed

)

67

T a b

le 2 .

(c o n ti n u e d )

A u th

o r

(Y e ar

) N

S am

p le

T im

in g

M e n ta

l H

e al

th O

u tc

o m

e s

(M e as

u re

; C

la ss

if ic

at io

n S ys

te m

) P re

va le

n ce

P re

d ic

to rs

1 9 9 2 —

C o u rt

h o u se

in S t.

L o u is

, M

is so

u ri

(1 )

Jo h n so

n , N

o rt

h ,

an d

S m

it h

(2 0 0 2 )

8 0

E m

p lo

ye e s

at co

u rt

h o u se

an d

o ff ic

e s

o f in

vo lv

e d

in d iv

id u al

s; su

b sa

m p le

co m

p le

te d

2 w

av e s

(n ¼

7 7 ;

a ff ec

te d )

6 – 8

w e e k s,

1 ye

ar ,

3 ye

ar s

P T

S D

, M

D , P D

, G

A D

, A

U D

, D

U D

(D IS

/D is

as te

r su

p p le

m e n t)

A t

6 – 8

w e e k s—

P T

S D

: 5 %

, M

D : 4 %

; P D

: 1 %

; G

A D

: 0 %

; A

U D

: 9 %

; D

U D

: 0 %

; A

t e it h e r

6 – 8

w e e k s,

1 ye

ar ,

o r

3 ye

ar s—

P T

S D

: 1 0 %

P T

S S , 6 – 8

w e e k s:

yo u n ge

r ag

e , b e in

g m

ar ri

e d ,l

o w

e r

e d u ca

ti o n ,f

e e lin

g lik

e th

e in

ci d e n t

h ad

ca u se

d th

e m

a gr

e at

d e al

o f

h ar

m (t

o ta

l P T

S S , re

e x p e ri

e n ci

n g)

, re

p o rt

in g

th at

th e

in ci

d e n t

w as

ve ry

u p se

tt in

g (a

vo id

an ce

), p e rc

e iv

e d

la ck

o f

re co

ve ry

(a vo

id an

ce ),

m e n ta

l h e al

th se

rv ic

e u ti liz

at io

n (r

e e x p e ri

e n ci

n g,

av o id

an ce

, an

d h yp

e ra

ro u sa

l)

1 9 9 3 —

O ff ic

e b u ild

in g

in S an

F ra

n ci

sc o , C

A (1

) C

la ss

e n ,

K o o p m

an , H

al e s,

an d

S p ie

ge l(

1 9 9 8 )

3 6

O ff ic

e e m

p lo

ye e s;

su b sa

m p le

co m

p le

te d

2 w

av e s

(n ¼

3 2 ;

a ff ec

te d )

1 w

e e k , 7 – 1 0

m o n th

s P T

S D

(I E S , D

T S , D

S M

-I II -R

); A

S D

(S A

S R

Q )

A t

1 w

e e k —

A S D

: 3 3 .3

% P T

S D

, 7 – 1 0

m o n th

s: A

S D

sy m

p to

m s

(D T

S to

ta l,

IE S -R

in tr

u si

o n , an

d IE

S -R

av o id

an ce

)

1 9 9 4 —

B ro

o k ly

n B ri

d ge

in B ro

o k ly

n , N

Y (1

) T

ra p p le

r an

d F ri

e d n m

an (1

9 9 6 )

2 2

Y o u th

w h o

w e re

in th

e va

n th

at w

as ta

rg e t

o f sh

o o ti n g

(s u rv

iv o rs

); 1 1

st u d e n ts

, ag

e -m

at ch

e d

an d

fr o m

th e

sa m

e co

m m

u n it y

(c o m

p ar

is o n ; a ff ec

te d )

8 w

e e k s

P T

S D

(D S M

-I V

; P T

S D

sy m

p to

m sc

al e , IE

S -R

, cl

in ic

al in

fo rm

at io

n );

M D

(B D

I, cl

in ic

al in

fo rm

at io

n ),

G A

D sy

m p to

m s

(B A

I, cl

in ic

al in

fo rm

at io

n )

A m

o n g

su rv

iv o rs

— P T

S D

: 3 6 .4

% ; M

D : 4 5 .5

% ;

A d ju

st m

e n t

D is

o rd

e r

w it h

an x ie

ty : 9 .1

% ; A

d ju

st m

e n t

d is

o rd

e r

w it h

m ix

e d

an x ie

ty an

d d e p re

ss e d

m o o d : 9 .1

%

P T

S S : b e in

g a

su rv

iv o r

(v s.

m e m

b e r

o f

co m

p ar

is o n

gr o u p ; in

tr u si

o n

an d

av o id

an ce

); M

D sy

m p to

m s:

b e in

g a

su rv

iv o r

(v s.

m e m

b e r

o f co

m p ar

is o n

gr o u p );

G A

D sy

m p to

m s:

b e in

g a

su rv

iv o r

(v s.

m e m

b e r

o f co

m p ar

is o n

gr o u p )

1 9 9 9 —

H ig

h sc

h o o l in

C o lu

m b in

e , C

O (1

) S tr

e te

sk y

an d

H o ga

n (2

0 0 1 )

1 2 2

F e m

al e

co lle

ge st

u d e n t

at R

o ch

e st

e r

In st

it u te

o f

T e ch

n o lo

gy , as

se ss

e d

p re

- in

ci d e n t

(n ¼

2 0 )

an d

p o st

- in

ci d e n t

(n ¼

1 0 2 ; re

m o te

)

(v ar

ie d )

P e rc

e iv

e d

sa fe

ty (6

it e m

s) —

P e rc

e iv

e d

sa fe

ty : p re

-i n ci

d e n t

sa m

p le

(v s.

p o st

-i n ci

d e n t

sa m

p le

), b e in

g in

th e

F in

e A

rt s

o r

L an

gu ag

e an

d L it e ra

tu re

d e p ar

tm e n ts

(v s.

th e

S o ci

o lo

gy d e p ar

tm e n t)

(2 )

B re

n e r,

S im

o n ,

A n d e rs

o n ,

B ar

ri o s,

an d

S m

al l

(2 0 0 2 )

1 5 ,3

4 9

P ar

ti ci

p an

ts in

th e

1 9 9 9

n at

io n al

sc h o o l- b as

e d

Y o u th

R is

k B e h av

io r

S u rv

e y,

as se

ss e d

p re

- in

ci d e n t

(n ¼

1 2 .0

4 9 )

an d

p o st

-i n ci

d e n t

(n ¼

3 ,3

0 0 ;

re m

o te

)

(v ar

ie d )

In te

rp e rs

o n al

vi o le

n ce

(8 it e m

s) , S u ic

id e

(5 it e m

s) —

It e m

‘‘f e lt

to o

u n sa

fe to

go to

sc h o o l’’

: p o st

- in

ci d e n t

sa m

p le

(v s.

p re

-i n ci

d e n t

sa m

p le

), e ff e ct

st ro

n ge

r in

ru ra

l (v

s. su

b u rb

an an

d u rb

an )

ar e as

. It

e m

‘‘c o n si

d e re

d su

ic id

e ’’:

p re

-i n ci

d e n t

sa m

p le

(v s.

p o st

-i n ci

d e n t

sa m

p le

), e ff e ct

o n ly

in su

b u rb

an an

d ru

ra l ar

e as

. It

e m

‘‘m ad

e a

su ic

id e

p la

n ’’:

p re

-i n ci

d e n t

sa m

p le

(v s.

p o st

-i n ci

d e n t

sa m

p le

), e ff e ct

o n ly

in su

b u rb

an an

d ru

ra l ar

e as (c o n ti n u ed

)

68

T a b

le 2 .

(c o n ti n u e d )

A u th

o r

(Y e ar

) N

S am

p le

T im

in g

M e n ta

l H

e al

th O

u tc

o m

e s

(M e as

u re

; C

la ss

if ic

at io

n S ys

te m

) P re

va le

n ce

P re

d ic

to rs

(3 )

A d d in

gt o n

(2 0 0 3 )

8 ,3

9 7

P ar

ti ci

p an

ts in

th e

1 9 9 9

S ch

o o l

C ri

m e

S u p p le

m e n t

to th

e N

at io

n al

C ri

m e

V ic

ti m

iz at

io n

S u rv

e y,

as se

ss e d

p re

-i n ci

d e n t

(n ¼

5 ,6

2 0 )

an d

p o st

- in

ci d e n t

(n ¼

2 ,7

7 7 ; re

m ot

e)

(v ar

ie d )

A vo

id an

ce (7

it e m

s) , F e ar

o f

vi ct

im iz

at io

n (2

it e m

s) —

It e m

‘‘h o w

o ft

e n

ar e

yo u

af ra

id th

at so

m e o n e

w ill

at ta

ck o r

h ar

m yo

u at

sc h o o l? ’’:

p o st

-i n ci

d e n t

sa m

p le

(v s.

p re

- in

ci d e n t

sa m

p le

)

2 0 0 6 —

D aw

so n

C o lle

ge (D

C )

in M

o n tr

e al

, Q

u e b e c

(1 )

S é gu

in e t

al .

(2 0 1 3 )

9 4 8

D C

st u d e n ts

an d

e m

p lo

ye e s

(a ff ec

te d )

1 8

m o n th

s L if e ti m

e an

d p o st

-i n ci

d e n t

p sy

ch ia

tr ic

d is

o rd

e rs

(m e as

u re

s ad

ap te

d fr

o m

th e

2 0 0 2

C an

ad ia

n C

o m

m u n it y

H e al

th S u rv

e y)

P re

va le

n ce

o f an

y p sy

ch ia

tr ic

d is

o rd

e r:

3 0 %

; P o st

- in

ci d e n t

in ci

d en

ce ra

te s—

P T

S D

: 1 .8

% ; M

D : 5 %

; A

lc o h o l d e p e n d e n cy

: 5 %

; S o ci

al p h o b ia

: 3 %

; A

n y

p sy

ch ia

tr ic

d is

o rd

e r

at p o st

-i n ci

d e n t,

w it h

p re

- in

ci d e n t

o n se

t: 1 2 %

In ci

d e n ce

o f an

y p sy

ch ia

tr ic

d is

o rd

e r:

G re

at e r

an d

cl o se

r e x p o su

re (s

ta ti st

ic s

n o t

re p o rt

ed )

2 0 0 7 —

H ig

h sc

h o o l in

Jo k e la

, F in

la n d

(1 a)

H ar

av u o ri

, S u o m

al ai

n e n ,

B e rg

, K

iv ir

u u su

, an

d M

ar tt

u n e n

(2 0 1 1 )

2 3 1

a 4

m o n th

s P o st

tr au

m at

ic d is

tr e ss

(I E S );

P T

S D

(I E S );

P sy

ch ia

tr ic

d is

tu rb

an ce

(G H

Q )

— P o st

tr au

m at

ic d is

tr e ss

: b e in

g ap

p ro

ac h e d

o r

in te

rv ie

w e d

b y

jo u rn

al is

ts ; P sy

ch ia

tr ic

d is

tu rb

an ce

: h ig

h e r

m e d ia

e x p o su

re

(1 b )

S u o m

al ai

n e n ,

H ar

av u o ri

, B e rg

, K

iv ir

u u su

, an

d M

ar tt

u n e n

(2 0 1 1 )

2 3 1

Jo k e la

H ig

h S ch

o o l st

u d e n ts

. U

n e x p o se

d co

m p ar

is o n

gr o u p

o f st

u d e n ts

fr o m

a d if fe

re n t

h ig

h sc

h o o l in

F in

la n d

(n ¼

5 2 6 ; a ff ec

te d )

4 m

o n th

s P o st

tr au

m at

ic d is

tr e ss

(I E S );

P T

S D

(I E S );

P sy

ch ia

tr ic

d is

tu rb

an ce

(G H

Q );

C h an

ge s

in su

b st

an ce

ab u se

d u ri

n g

p as

t 6

m o n th

s (1

it e m

)

A m

o n g

e x p o se

d —

P o st

tr au

m at

ic d is

tr e ss

: 4 2 .8

% ; P T

S D

: 1 9 .2

% ;

P sy

ch ia

tr ic

d is

tu rb

an ce

: 3 1 .7

% ; In

cr e as

e in

su b st

an ce

ab u se

d u ri

n g

p as

t 6

m o n th

s: 1 3 .3

%

P o

st tr

au m

at ic

d is

tr e ss

: E x p o

se d

(v s.

u n e x p o se

d );

P T

S D

: fe

m al

e ge

n d e r,

e x p o se

d (v

s. u n e x p o se

d ),

se ve

re o r

e x tr

e m

e e x p o

su re

(v s.

m il d

to si

gn if ic

an t

e x p o su

re ),

lo w

e r

p e rc

e iv

e d

su p p o rt

fr o m

fa m

il y

an d

fr ie

n d s;

P sy

ch ia

tr ic

d is

tu rb

a n c e : o ld

e r

ag e , fe

m al

e ge

n d e r,

li vi

n g

w it

h o n e

b io

lo g ic

al p a re

n t

o r

o th

e rw

is e

(v s.

li vi

n g

w it

h b o

th b io

lo g ic

al p a re

n ts

), e x p o se

d (v

s. u n e x p o

se d ),

lo w

e r

p e rc

e iv

e d

so c ia

l su

p p o

rt fr

o m

fa m

il y,

p re

v io

u s

m e n ta

l su

p p o

rt fr

o m

a n o

n gu

a rd

ia n

ad u lt

(1 c)

M u rt

o n e n ,

S u o m

al ai

n e n ,

H ar

av u o ri

, an

d M

ar tt

u n e n

(2 0 1 2 )

Jo k e la

H ig

h S ch

o o l st

u d e n ts

(a ff ec

te d )

4 m

o n th

s P o st

tr au

m at

ic d is

tr e ss

(I E S );

P T

S D

(I E S );

P sy

ch ia

tr ic

d is

tu rb

an ce

(G H

Q )

— P o st

tr au

m at

ic d is

tr e ss

: h av

in g

b e e n

o ff e re

d cr

is is

su p p o rt

; P T

S D

: n o t

p e rc

e iv

in g

cr is

is su

p p o rt

as h e lp

fu l;

P sy

ch ia

tr ic

d is

tu rb

an ce

: h av

in g

b e e n

o ff e re

d cr

is is

su p p o rt

, n o t

p e rc

e iv

in g

cr is

is su

p p o rt

as h e lp

fu l

(c o n ti n u ed

)

69

T a b

le 2 .

(c o n ti n u e d )

A u th

o r

(Y e ar

) N

S am

p le

T im

in g

M e n ta

l H

e al

th O

u tc

o m

e s

(M e as

u re

; C

la ss

if ic

at io

n S ys

te m

) P re

va le

n ce

P re

d ic

to rs

2 0 0 7 —

V ir

gi n ia

T e ch

(V T

) in

B la

ck sb

u rg

, V

A (1

a) F al

la h i an

d L e si

k (2

0 0 9 )

3 1 2

S tu

d e n ts

fr o m

C e n tr

al C

o n n e ct

ic u t

S ta

te U

n iv

e rs

it y

(r em

o te

)

3 w

e e k s

A S D

(1 3 -i te

m s,

D S M

-I V

) —

A S D

sy m

p to

m s:

o ld

e r

ag e

(n ig

h tm

ar e s)

, fe

m al

e ge

n d e r

(f e ar

), ra

ci al

/e th

n ic

m in

o ri

ty st

at u s

(s u ic

id al

id e at

io n ,

re p la

yi n g

th e

e ve

n t)

, m

o re

h o u rs

o f T

V w

at ch

in g

(i n tr

u si

ve th

o u gh

ts , sl

e e p

d is

tu rb

an ce

s, d is

tr ac

ti o n , fe

ar , st

o m

ac h

u p se

t, d e p re

ss io

n , d is

o rg

an iz

at io

n ,

re p la

yi n g

o f th

e e ve

n t,

an d

an ge

r) (1

b )

F al

la h i,

A u st

ad ,

F al

lo n , an

d L e is

h m

an (2

0 0 9 )

3 1 2

a 3

w e e k s

P sy

ch ia

tr ic

sy m

p to

m s

(u n sp

e ci

fi e d )

— P sy

ch ia

tr ic

sy m

p to

m s:

fe ar

s o f b e in

g p e rs

o n al

ly h ar

m e d

o n

ca m

p u s,

fe ar

s th

at a

si m

ila r

in ci

d e n t co

u ld

o cc

u r

o n

ca m

p u s,

gr e at

e r

e x p o su

re to

n e w

s m

e d ia

,g re

at e r

ti m

e d is

cu ss

in g

th e

in ci

d e n t

w it h

fa m

ily ,

gr e at

e r

ti m

e d is

cu ss

in g

th e

in ci

d e n t

w it h

fr ie

n d s

(2 a)

L it tl e to

n ,

A x so

m , an

d G

ri lls

-T aq

u e ch

e l

(2 0 0 9 )

1 9 3

F e m

al e

V T

st u d e n ts

(a ff ec

te d )

P re

-i n ci

d e n t,

2 m

o n th

s, 6

m o n th

s

M D

(C E S -D

); G

A D

(F D

A S )

— P sy

ch o lo

gi ca

l d is

tr e ss

(l at

e n t

va ri

ab le

o f

M D

an d

G A

D sy

m p to

m su

b sc

al e s)

, 6

m o n th

s: h ig

h e r

re so

u rc

e lo

ss at

2 an

d 6

m o n th

s, lo

w e r

re so

u rc

e ga

in at

2 an

d 6

m o n th

s (2

b ) L it tl e to

n , G

ri lls

- T

aq u e ch

e l,

an d

A x so

m (2

0 0 9 )

2 9 3

a P re

-i n ci

d e n t,

2 m

o n th

s, 6

m o n th

s

P T

S D

(D S M

-I V

; P S S -S

R )

A t

2 m

o n th

s— P T

S D

: 3 0 %

; A

t 6

m o n th

s— P T

S D

: 2 3 %

P T

S S , 2

m o n th

s: H

ig h e r

re so

u rc

e lo

ss at

2 m

o n th

s p o st

-i n ci

d e n t.

P T

S S , 6

m o n th

s: h ig

h e r

re so

u rc

e lo

ss at

2 an

d 6

m o n th

s (2

c) G

ri lls

- T

aq u e ch

e l,

L it tl e to

n , an

d A

x so

m (2

0 1 1 )

2 9 8

a P re

-i n ci

d e n t,

2 m

o n th

s, 6

m o n th

s

G A

D (F

D A

S );

Q u al

it y

o f L if e

(W H

O -Q

O L )

— G

A D

sy m

p to

m s,

2 m

o n th

s (e

m o ti o n al

, p h ys

io lo

gi ca

l, co

gn it iv

e , an

d b e h av

io ra

l su

b sc

al e s)

: h ig

h e r

p re

-s h o o ti n g

G A

D sy

m p to

m s

(a ll

su b sc

al e s)

, h ig

h e r

e x p o su

re (b

e h av

io ra

l) , lo

w e r

se lf -w

o rt

h (a

ll su

b sc

al e s)

, h ig

h e r

se n se

o f

ra n d o m

n e ss

(e m

o ti o n al

), lo

w e r

fa m

ily su

p p o rt

(e m

o ti o n al

, p h ys

io lo

gi ca

l, co

gn it iv

e );

Q u al

it y

o f L if e , 2

m o n th

s (p

h ys

ic al

, p sy

ch o lo

gi ca

l, so

ci al

, an

d e n vi

ro n m

e n t

su b sc

al e s)

: lo

w e r

e x p o su

re (p

h ys

ic al

), h ig

h e r

se lf -w

o rt

h (a

ll su

b sc

al e s)

, lo

w e r

se n se

o f ra

n d o m

n e ss

(p h ys

ic al

, p sy

ch o lo

gi ca

l) , h ig

h e r

fa m

ily su

p p o rt

(a ll

su b sc

al e s)

, h ig

h e r

fr ie

n d

su p p o rt

(e n vi

ro n m

e n t)

(c o n ti n u ed

)

70

T a b

le 2 .

(c o n ti n u e d )

A u th

o r

(Y e ar

) N

S am

p le

T im

in g

M e n ta

l H

e al

th O

u tc

o m

e s

(M e as

u re

; C

la ss

if ic

at io

n S ys

te m

) P re

va le

n ce

P re

d ic

to rs

(2 d )

L it tl e to

n ,

A x so

m , an

d G

ri lls

-T aq

u e ch

e l

(2 0 1 1 )

3 6 8

a P re

-i n ci

d e n t,

2 m

o n th

s, 6

m o n th

s, 1

ye ar

P T

S D

(D S M

-I V

; P S S -S

R );

M D

(C E S -D

); G

A D

(F D

A S )

A t

2 m

o n th

s— M

D : 1 9 %

; A

t 6

m o n th

s— M

D : 2 2 %

; A

t 1

ye ar

— P T

S D

: 2 7 %

, M

D :

2 4 %

P T

S S , 6

m o n th

s: P T

S S

at 2

m o n th

s, m

al ad

ap ti ve

co p in

g at

2 m

o n th

s; P T

S S , 1

ye ar

: P T

SS an

d m

al ad

ap ti ve

co p in

g at

6 m

o n th

s; P sy

ch o lo

gi ca

l d is

tr e ss

(l at

e n t

va ri

ab le

o f M

D an

d G

A D

sy m

p to

m su

b sc

al e s)

, 2

m o n th

s: p re

-i n ci

d e n t

d is

tr e ss

; P sy

ch o lo

gi ca

l d is

tr e ss

, 6

m o n th

s: P sy

ch o lo

gi ca

l d is

tr e ss

an d

m al

ad ap

ti ve

co p in

g at

2 m

o n th

s; P sy

ch o lo

gi ca

l d is

tr e ss

,1 ye

ar :P

sy ch

o lo

gi ca

ld is

tr e ss

an d

m al

ad ap

ti ve

co p in

g at

6 m

o n th

s (2

e ) L it tl e to

n , G

ri lls

- T

aq u e ch

e l,

A x so

m , B ye

, an

d B u ck

(2 0 1 2 )

2 1 5

a P re

-i n ci

d e n t,

2 m

o n th

s, 6

m o n th

s, 1

ye ar

P T

S D

(D S M

-I V

; P S S -S

R );

M D

(C E S -D

) —

P T

S S , 1

ye ar

: p re

-i n ci

d e n t

se x u al

vi ct

im iz

at io

n , lo

w e r

b e n e vo

le n ce

b e lie

fs at

2 m

o n th

s, lo

w e r

fa m

ily su

p p o rt

at 2

m o n th

s; M

D sy

m p to

m s,

1 ye

ar : p re

- in

ci d e n t

se x u al

vi ct

im iz

at io

n , lo

w e r

b e n e vo

le n ce

b e lie

fs at

2 m

o n th

s, lo

w e r

fa m

ily su

p p o rt

at 2

m o n th

s (3

a) H

u gh

e s

e t

al .

(2 0 1 1 )

4 ,6

3 9

V T

st u d e n ts

(a ff e ct

e d )

3 – 4

m o n th

s, 1

ye ar

P T

S D

(T S Q

, D

S M

-I V

) P T

S D

: 1 5 .4

% P T

S D

: fe

m al

e ge

n d e r,

h ig

h e r

e x p o su

re to

fi rs

t in

ci d e n t

o f at

ta ck

, in

ab ili

ty to

co n ta

ct cl

o se

fr ie

n d s

d u ri

n g

in ci

d e n t,

d e at

h o f a

cl o se

fr ie

n d , d e at

h o f a

fr ie

n d

o f ac

q u ai

n ta

n ce

(3 b )

S m

it h , A

b e yt

a, H

u gh

e s,

an d

Jo n e s

(2 0 1 4 )

2 4 5

S u b sa

m p le

o f b e re

av e d

p ar

ti ci

p an

ts w

h o

co m

p le

te d

fo llo

w -u

p as

se ss

m e n ts

(a ff ec

te d )a

3 – 4

m o n th

s, 1

ye ar

P T

S D

(T S Q

, D

S M

-I V

); G

ri e f

(8 -i te

m m

e as

u re

) —

G ri

e f se

ve ri

ty : h ig

h e r

P T

S S

at 3 – 4

m o n th

s, lo

w e r

se lf -e

ff ic

ac y,

gr e at

e r

d is

ru p te

d w

o rl

d vi

e w

(4 a)

H aw

d o n

an d

R ya

n (2

0 1 1 )

3 6 3

V T

st u d e n ts

an d

fa cu

lt y

(a ff ec

te d )

5 m

o n th

s, 9

m o n th

s, an

d 1 3

m o n th

s

E m

o ti o n al

an d

b e h av

io ra

l w

e ll-

b e in

g (C

D C

d e p re

ss io

n sc

re e n e r,

W A

I, it e m

as se

ss in

g p ro

d u ct

iv it y)

— L o w

e r

e m

o ti o n al

an d

b e h av

io ra

l w

e ll-

b e in

g, 5

m o n th

s, 9

m o n th

s, an

d 1 3

m o n th

s: lo

w e r

so ci

al so

lid ar

it y

at 5

m o n th

s, 9

m o n th

s, an

d 1 3

m o n th

s

(4 b )

H aw

d o n

an d

R ya

n (2

0 1 2 )

5 4 3

V T

st u d e n ts

(a ff ec

te d )

5 m

o n th

s E m

o ti o n al

an d

b e h av

io ra

l w

e ll-

b e in

g (C

D C

d e p re

ss io

n sc

re e n e r,

W A

I, it e m

as se

ss in

g p ro

d u ct

iv it y)

— L o w

e r

e m

o ti o n al

an d

b e h av

io ra

l w

e ll-

b e in

g: fe

m al

e ge

n d e r,

k n o w

in g

a vi

ct im

o f

th e

in ci

d e n t,

lo w

e r

o ve

ra ll

so ci

al su

p p o rt

, la

ck o f p ar

ti ci

p at

io n

o n

a co

m m

u n it y

te am

, h av

in g

se e n

a p ro

fe ss

io n al

co u n se

lo r

af te

r th

e in

ci d e n t,

fe w

e r

in -p

e rs

o n

co n ve

rs at

io n s

w it h

fa m

ily , fe

w e r

vi rt

u al

co n ve

rs at

io n s

w it h

fa m

ily , fe

w e r

vi rt

u al

co n ve

rs at

io n s

w it h

fr ie

n d s,

an d

lo w

e r

so ci

al so

lid ar

it y

(c o n ti n u ed

)

71

T a b

le 2 .

(c o n ti n u e d )

A u th

o r

(Y e ar

) N

S am

p le

T im

in g

M e n ta

l H

e al

th O

u tc

o m

e s

(M e as

u re

; C

la ss

if ic

at io

n S ys

te m

) P re

va le

n ce

P re

d ic

to rs

2 0 0 8 —

N o rt

h e rn

Il lin

o is

U n iv

e rs

it y

(N IU

) in

D e K

al b , IL

(1 a)

S te

p h e n so

n ,

V al

e n ti n e r,

K u m

p u la

, an

d O

rc u tt

(2 0 0 9 )

6 9 1

F e m

al e

N IU

st u d e n ts

(a ff ec

te d )

P re

-i n ci

d e n t,

2 – 4

w e e k s

P T

S D

(D E Q

, D

S M

-I V

) —

P T

S S , 2 – 4

w e e k s:

h ig

h e r

an x ie

ty se

n si

ti vi

ty (p

h ys

ic al

an d

co gn

it iv

e co

n ce

rn s)

, h ig

h e r

e x p o su

re

(1 b )

F e rg

u s,

R ab

e n h o rs

t, O

rc u tt

, an

d V

al e n ti n e r

(2 0 1 1 )

5 8

S u b sa

m p le

o f p ar

ti ci

p an

ts w

it h

h ig

h e st

an d

lo w

e st

le ve

ls o f e x p o su

re p ar

ti ci

p at

e d

in a

la b o ra

to ry

e x p e ri

m e n t

(a ff ec

te d )a

6 w

e e k s

P T

SD (D

E Q

, D

SM -I V

); M

D (D

A SS

-2 1 );

G A

D (D

A SS

-2 1 )

— P T

S S , 6

w e e k s:

H ig

h e r

n e ga

ti ve

af fe

ct w

h ile

w ri

ti n g

an d

re ad

in g

ab o u t

e ve

n t;

M D

sy m

p to

m s,

6 w

e e k s:

H ig

h e r

n e ga

ti ve

af fe

ct w

h ile

re ad

in g

ab o u t

th e

in ci

d e n t;

G A

D sy

m p to

m s,

6 w

e e k s:

H ig

h e r

n e ga

ti ve

af fe

ct w

h ile

w ri

ti n g

an d

re ad

in g

ab o u t

th e

in ci

d e n t

(1 c)

K u m

p u la

, O

rc u tt

, B ar

d e e n ,

an d

V ar

k o vi

tz k y

(2 0 1 1 )

5 3 2

a P re

-i n ci

d e n t,

2 – 4

w e e k s,

8 m

o n th

s

P T

S D

(D E Q

, D

S M

-I V

) P re

-i n ci

d e n t—

S ig

n if ic

an t

P T

S S : 2 0 .8

% ; A

t 2 – 4

w e e k s—

S ig

n if ic

an t

P T

S S :

4 9 .4

% ; A

t 8

m o n th

s— S ig

n if ic

an t

P T

S S : 1 1 .4

%

P T

S S ,

2 – 4

w e e k s:

n o

n -W

h it

e ra

ce /

e th

n ic

it y

(a vo

id an

c e

an d

h y p e ra

ro u sa

l) ,

h ig

h e r

p re

-i n ci

d e n t

tr au

m a

e x p o

su re

, h ig

h e r

p re

-i n ci

d e n t

e x p e ri

e n ti

a l

av o id

a n c e ,

h ig

h e r

p e ri

tr a u m

at ic

d is

so c ia

ti o

n ;

P T

S S ,

8 m

o n th

s: h ig

h e r

e x p o su

re ,

h ig

h e r

P T

S S

at 2 – 4

w e e k s,

h ig

h e r

e x p e ri

e n ti

a l

av o id

an c e

at 2 – 4

w e e k s

(1 d )

L it tl e to

n ,

K u m

p u la

, an

d O

rc u tt

(2 0 1 1 )

6 9 1

a P re

-i n ci

d e n t,

2 – 4

w e e k s,

8 m

o n th

s

P T

S D

(D E Q

, D

S M

-I V

— P T

S S ,

2 – 4

w e e k s:

n o

n -A

fr ic

a n

A m

e ri

ca n

ra ce

/e th

n ic

it y ,

h ig

h e r

p re

-i n c id

e n t

tr au

m a

e x p o

su re

, h ig

h e r

p re

-i n ci

d e n t

st re

ss ,

h ig

h e r

e x p o su

re ;

P T

S S ,

8 m

o n th

s: A

si a n

A m

e ri

c an

ra ce

/e th

n ic

it y,

h ig

h e r

p re

-i n ci

d e n t

tr au

m a

e x p o

su re

, h ig

h e r

p re

-i n ci

d e n t

G A

D sy

m p to

m s,

h ig

h e r

e x p o

su re

, h ig

h e r

P T

S S

at 2 – 4

w e e k s,

h ig

h e r

re so

u rc

e lo

ss (1

e )

M e rc

e r

e t

al .

(2 0 1 2 )

2 3 5

S u b sa

m p le

o f p ar

ti ci

p an

ts w

h o

p ro

vi d e d

D N

A sa

m p le

s (a

ff ec

te d )a

P re

-i n ci

d e n t,

2 – 4

w e e k s

P T

S D

(D E Q

, D

S M

-I V

) —

P T

S S ,

ch an

ge in

sy m

p to

m s

fr o m

p re

- in

ci d e n t

to 2 – 4

w e e k s:

rs 2 5 5 3 1

A /A

ge n o

ty p e , 5 -H

T T

L P R

m u lt

im ar

k e r

lo w

- e x p re

ss in

g ge

n o

ty p e s

(c o n ti n u ed

)

72

T a b

le 2 .

(c o n ti n u e d )

A u th

o r

(Y e ar

) N

S am

p le

T im

in g

M e n ta

l H

e al

th O

u tc

o m

e s

(M e as

u re

; C

la ss

if ic

at io

n S ys

te m

) P re

va le

n ce

P re

d ic

to rs

(1 f)

B ar

d e e n ,

K u m

p u la

, an

d O

rc u tt

(2 0 1 3 )

6 9 1

a P re

-i n ci

d e n t,

2 – 4

w e e k s,

8 m

o n th

s

P T

S D

(D E Q

, D

S M

-I V

); M

D (D

A S S -2

1 );

G A

D (D

A S S -

2 1 );

S tr

e ss

(D A

S S -2

1 )

P T

S S ,

2 – 4

w e e k s:

h ig

h e r

p re

-i n ci

d e n t

p o

st tr

au m

at ic

st re

ss ,

h ig

h e r

e x p o

su re

, h ig

h e r

e m

o ti

o n

re gu

la ti

o n

d if fi cu

lt ie

s at

p re

-i n ci

d e n t

an d

2 – 4

w e e k s;

P T

S S ,

h ig

h e r

e m

o ti

o n

re gu

la ti

o n

d if fi cu

lt ie

s at

2 – 4

w e e k s

an d

8 m

o n th

s; G

e n e ra

l D

is tr

e ss

(l at

e n t

co n st

ru c t

o f

M D

, G

A D

, an

d st

re ss

), 2 – 4

w e e k s:

p re

- in

ci d e n t

ge n e ra

l d is

tr e ss

, h ig

h e r

e x p o su

re ,

h ig

h e r

e m

o ti

o n

re gu

la ti

o n

d if fi c u lt

ie s

at 2 – 4

w e e k s;

G e n e ra

l d is

tr e ss

(l at

e n t

co n st

ru c t

o f

M D

, G

A D

, an

d st

re ss

), 8

m o n th

s: h ig

h e r

e m

o ti

o n

re gu

la ti

o n

d if fi cu

lt ie

s at

2 – 4

m o

n th

s an

d 8

m o n th

s (1

g) O

rc u tt

, B o n an

n o , H

an n a,

an d

M ir

o n

(2 0 1 4 )

6 6 0

a P re

-i n ci

d e n t,

2 – 4

w e e k s,

8 m

o n th

s, 1 4

m o n th

s, 2 0

m o n th

s, 2 6

m o n th

s, an

d 3 2

m o n th

s

P T

S D

(D E Q

, D

S M

-I V

) —

P o st

tr au

m at

ic st

re ss

, ch

ro n ic

d ys

fu n ct

io n

tr aj

e ct

o ry

: P re

-i n ci

d e n t

tr au

m a

e x p o su

re , h ig

h e r

p re

-i n ci

d e n t

e x p e ri

e n ti al

av o id

an ce

, h ig

h e r

e x p o su

re ,

h ig

h e r

e m

o ti o n

re gu

la ti o n

d if fi cu

lt ie

s (l im

it e d

ac ce

ss to

st ra

te gi

e s,

la ck

o f

e m

o ti o n al

cl ar

it y)

at 8

m o n th

s (2

) H

ar tn

e tt

an d

S k o w

ro n sk

i (2

0 1 0 )

5 5

N IU

st u d e n ts

(a ff ec

te d )

P re

-i n ci

d e n t,

2 – 3

w e e k s

M o o d

(P o M

S )

— —

2 0 0 8 —

C e n tr

al A

rk an

sa s

U n iv

e rs

it y

(C A

U )

in C

o n w

ay , A

R (1

) M

cI n ty

re ,

S p e n ce

, an

d L ac

h la

n (2

0 1 1 )

5 6 9

C A

U st

u d e n ts

(a ff ec

te d )

1 w

e e k

E m

o ti o n al

R e ac

ti o n s

(7 -i te

m sc

al e )

— E m

o ti o n al

re ac

ti o n s:

fe m

al e

ge n d e r

(c o n fu

si o n , fe

ar , sa

d n e ss

, la

ck o f

ca lm

n e ss

, an

d p an

ic )

2 0 0 8 —

S e in

äj o k i U

n iv

e rs

it y

o f A

p p lie

d S ci

e n ce

s (S

U A

S )

in K

au h aj

o k i,

F in

la n d

(1 )

T u ru

n e n ,

H ar

av u o ri

, P u n am

äk i,

S u o m

al ai

n e n , an

d M

ar tt

u n e n

(2 0 1 4 )

1 3 7

S U

A S

st u d e n ts

(a ff ec

te d )

4 m

o n th

s, 1 6

m o n th

s, an

d 2 8

m o n th

s

P T

S D

(I E S );

D is

so ci

at iv

e sy

m p to

m s

(A -D

E S ),

P T

G (P

T G

I)

— P T

S S , 4

m o n th

s: p re

o c cu

p ie

d at

ta ch

m e n t

st y le

(t o ta

l P T

S S , av

o id

an c e

su b sc

a le

); D

is so

c ia

ti ve

sy m

p to

m s,

4 m

o n th

s: n o

n se

c u re

at ta

ch m

e n t

st y le

s; D

is so

c ia

ti ve

sy m

p to

m s,

1 6

m o

n th

s: n o

n se

c u re

at ta

ch m

e n t

st y le

s; L o

w e r

P T

G , 1 6

m o

n th

s: av

o id

an t

at ta

c h m

e n t

st y le

(r e la

ti n g

to o th

e rs

su b sc

al e );

L o

w e r

P T

G , 2 8

m o

n th

s: av

o id

an t

at ta

ch m

e n t

st yl

e (r

e la

ti n g

to o th

e rs

su b sc

al e )

(c o n ti n u ed

)

73

T a b

le 2 .

(c o n ti n u e d )

A u th

o r

(Y e ar

) N

S am

p le

T im

in g

M e n ta

l H

e al

th O

u tc

o m

e s

(M e as

u re

; C

la ss

if ic

at io

n S ys

te m

) P re

va le

n ce

P re

d ic

to rs

2 0 0 7

an d

2 0 0 8 —

S ch

o o ls

in Jo

le k a

an d

K au

h aj

o k i,

F in

la n d

(c o m

b in

e d )

(1 )

V u o ri

, H

aw d o n ,

A tt

e , an

d R

äs än

e n

(2 0 1 3 )

6 4 9

R an

d o m

sa m

p le

o f re

si d e n ts

in Jo

le k a

(n ¼

3 3 0 )

an d

K au

h aj

o k i (n ¼

3 9 1 ;

a ff ec

te d )

6 – 7

m o n th

s W

o rr

y (3

it e m

s) —

W o rr

y (a

b o u t

te rr

o ri

sm , lo

ca l cr

im e , an

d sc

h o o l sh

o o ti n gs

): L o w

e r

so ci

al so

lid ar

it y,

m o re

p u n it iv

e at

ti tu

d e s

to w

ar d

cr im

e

2 0 0 7

an d

2 0 0 8 —

V T

an d

N IU

(c o m

b in

e d )

(1 )

K am

in sk

i, K

o o n s-

W it t,

T h o m

p so

n , an

d W

e is

s (2

0 1 0 )

1 ,9

5 2

C o lle

ge st

u d e n ts

fr o m

th e

U n iv

e rs

it y

o f S o u th

C ar

o lin

a (r

em o te

)

P re

-V ir

gi n ia

T e ch

, p o st

-V ir

gi n ia

T e ch

, p re

-N IU

, p o st

-N IU

(1 ti m

e p o in

t p e r

p ar

ti ci

p an

t)

F e ar

(5 it e m

s) —

F e ar

o f w

al k in

g al

o n e

d u ri

n g

th e

d ay

: p o st

- V

ir gi

n ia

T e ch

as se

ss m

e n t,

p re

-N IU

as se

ss m

e n t,

n o n -W

h it e

ra ce

/e th

n ic

it y,

re si

d e n ce

o n

ca m

p u s;

F e ar

o f w

al k in

g al

o n e

af te

r d ar

k : as

se ss

m e n t

af te

r V

ir gi

n ia

T e ch

, yo

u n ge

r ag

e , fe

m al

e ge

n d e r,

re si

d e n ce

o n

ca m

p u s;

F e ar

o f

cr im

e : p o st

-V ir

gi n ia

T e ch

as se

ss m

e n t,

yo u n ge

r ag

e , fe

m al

e ge

n d e r,

re si

d e n ce

o n

ca m

p u s;

F e ar

o f m

u rd

e r:

p o st

-V ir

gi n ia

T e ch

as se

ss m

e n t,

p o st

-N IU

as se

ss m

e n t,

yo u n ge

r ag

e , fe

m al

e ge

n d e r,

n o n -W

h it e

ra ce

/e th

n ic

it y,

re si

d e n ce

o n

ca m

p u s;

F e ar

o f w

e ap

o n

at ta

ck : p o st

-V ir

gi n ia

T e ch

as se

ss m

e n t,

p o st

-N IU

as se

ss m

e n t,

yo u n ge

r ag

e , fe

m al

e ge

n d e r

(2 )

V ic

ar y

an d

F ra

le y

(2 0 1 0 )

2 8 4

V T

(n ¼

1 2 4 )

an d

N IU

(n ¼

1 6 0 )

st u d e n ts

(a ff ec

te d )

2 w

e e k s

an d

8 w

e e k s

P T

S D

(P S S -S

R ),

M D

(C E S D

-1 0 )

A t

2 w

e e k s—

P T

S D

: 6 4 %

; M

D : 7 1 %

; A

t 8

w e e k s—

P T

S D

: 2 2 %

; M

D : 3 0 %

P T

S D

, 2

w e e k s:

F e m

al e

ge n d e r,

k n o w

in g

o n e

o f th

e vi

ct im

s; M

D sy

m p to

m s,

2 w

e e k s:

F e m

al e

ge n d e r,

k n o w

in g

o n e

o f

th e

vi ct

im s

N o te

.U n d e r

e ac

h e ve

n t,

n u m

b e ri

n g

is u se

d to

d e n o te

w h e n

st u d ie

s u se

d d at

a fr

o m

th e

sa m

e sa

m p le

,w it h

st u d ie

s p re

se n te

d in

ch ro

n o lo

gi ca

lo rd

e r

b y

p u b lic

at io

n d at

e .F

o r

e x am

p le

,f o r

th e

1 9 8 4

e le

m e n ta

ry sc

h o o ls

h o o ti n g

in L o s

A n ge

le s,

C A

, tw

o st

u d ie

s fr

o m

th e

sa m

e sa

m p le

ar e

lis te

d an

d la

b e le

d ac

co rd

in gl

y: (1

a) P yn

o o s

e t

al . (1

9 8 7 )

an d

(1 b )

N ad

e r,

P yn

o o s,

F ai

rb an

k s,

an d

F re

d e ri

ck (1

9 9 0 ).

W h e n

th e re

w e re

m u lt ip

le sa

m p le

s u n d e r

e ac

h e ve

n t,

th e

sa m

p le

s w

e re

o rd

e re

d ch

ro n o lo

gi ca

lly b y

p u b lic

at io

n d at

e o f th

e fi rs

t st

u d y

w it h in

e ac

h sa

m p le

. T

h e

ta b le

lis ts

b iv

ar ia

te as

so ci

at io

n s

o n ly

if m

u lt iv

ar ia

te re

su lt s

w e re

u n av

ai la

b le

; if

p re

va le

n ce

w as

re p o rt

e d

in m

u lt ip

le p u b lic

at io

n s

fo r

th e

sa m

e sa

m p le

,t h e

fi gu

re th

at in

cl u d e d

a h ig

h e r

# o f p ar

ti ci

p an

ts is

in cl

u d e d . A

A /A

D ¼

al co

h o l ab

u se

o r

d e p e n d e n ce

; A

S D ¼

ac u te

st re

ss d is

o rd

e r;

A S P D ¼

an ti so

ci al

p e rs

o n al

it y

d is

o rd

e r;

A U

D ¼

al co

h o l u se

d is

o rd

e r;

B A

I ¼

B e ck

A n x ie

ty In

ve n to

ry ; B D

I ¼

B e ck

D e p re

ss io

n In

ve n to

ry ; C

D C ¼

C e n te

rs fo

r D

is e as

e C

o n tr

o l;

C E S -D ¼

1 0 -i te

m C

e n te

r fo

r E p id

e m

io lo

gi c

S tu

d ie

s S h o rt

D e p re

ss io

n S ca

le ; D

A S S -2

1 ¼

D e p re

ss io

n an

d A

n x ie

ty S tr

e ss

S ca

le s-

2 1

it e m

ve rs

io n ; D

A /D

D ¼

d ru

g ab

u se

o r

d e p e n d e n ce

; D

E Q ¼

D is

tr e ss

in g

E ve

n ts

Q u e st

io n n ai

re ; D

IS ¼

d ia

gn o st

ic in

te rv

ie w

sc h e d u le

; D

T S ¼

D av

id so

n T

ra u m

a S ca

le ; D

U D ¼

d ru

g u se

d is

o rd

e r;

F D

A S ¼

F o u r

D im

e n si

o n al

A n x ie

ty S ca

le ; G

A D ¼

ge n e ra

liz e d

an x ie

ty d is

o rd

e r;

G H

Q ¼

G e n e ra

l H

e al

th Q

u e st

io n n ai

re ; IE

S ¼

Im p ac

t o f

E ve

n ts

S ca

le ; M

D ¼

m aj

o r

d e p re

ss io

n ; N

IU ¼

N o rt

h e rn

Il lin

o is

U n iv

e rs

it y;

P D ¼

p an

ic d is

o rd

e r;

P D

I ¼

p sy

ch ia

tr ic

d ia

gn o st

ic in

te rv

ie w

; P o M

S ¼

P ro

fi le

o f M

o o d

S ta

te s;

P T

G I ¼

P o st

tr au

m at

ic G

ro w

th In

ve n to

ry ; P S S -S

R ¼

P T

S D

S ym

p to

m S ca

le -S

e lf

R e p o rt

; P T

S D ¼

p o st

tr au

m at

ic st

re ss

d is

o rd

e r;

P T

S D

-R I ¼

; P o st

tr au

m at

ic S tr

e ss

-R e ac

ti o n

In d e x ; P T

S S ¼

p o st

tr au

m at

ic st

re ss

sy m

p to

m s/

se ve

ri ty

; S A

S R

Q ¼

S ta

n fo

rd A

cu te

S tr

e ss

R e ac

ti o n

Q u e st

io n n ai

re ; S T

A I ¼

S ta

te T

ra it

A n x ie

ty In

ve n to

ry ; T

S Q ¼

T ra

u m

a S cr

e e n in

g Q

u e st

io n n ai

re ; V

T ¼

V ir

gi n ia

T e ch

; W

A I ¼

W e in

b e rg

e r

A d ju

st m

e n t

In ve

n to

ry ; W

H O

-Q O

L ¼

W o rl

d H

e al

th O

rg an

iz at

io n

Q u al

it y

o f L if e

S ca

le – B ri

e f.

a S am

e sa

m p le

d e sc

ri p ti o n

as th

e p re

ce d in

g st

u d y.

74

(proposed) DSM-IV criteria, respectively (Schwarz & Kowalski,

1991a, 1991b).

Other Mental Health Outcomes

Although most studies in our review reported on symptoms and

prevalence estimates of psychiatric disorders, others included

mental health outcomes that were not specific to any disorder.

Fourteen studies (12 independent samples) utilized inventories

or items assessing constructs that cut across disorders, includ-

ing psychiatric disturbance, stress, grief, mood, emotional reac-

tions, worry, and fear (e.g., McIntyre, Spence, & Lachlan,

2011; Suomalainen, Haravuorti, Berg, Kiviruusu, & Marttunen,

2011; Vuori, Hawdon, Atte, & Räsänen, 2013). Four studies

(three independent samples) included positive indices of men-

tal health—emotional and behavioral well-being, quality of

life, and posttraumatic growth (Grills-Taquechel, Littleton,

& Axsom, 2011; Hawdon & Ryan, 2011, 2012; Turunen, Har-

avuori, Punamäki, Suomalainen, & Marttunen, 2014). Finally,

one study (Orcutt, Bonanno, Hanna, & Miron, 2014) utilized

trajectory analysis of PTSS over seven waves to (one pre- and

six post-incident) in the context of the NIU campus shooting.

The majority of participants (60.9%) were in a minimal impact resilience trajectory, reporting low levels of symptoms

at each wave and a small elevation in symptoms at the first

post-incident wave only.

Assessing the Mental Health Impact of Mass Shootings

In reviewing the studies, we noted how investigators assessed

whether participants’ symptoms reflected the impact of the mass

shooting, versus ongoing mental health difficulties that might

have been present before the incident took place. Certainly, per-

sonality disorders, which are conceptualized as enduring and

pervasive phenomenon, are unlikely to be the result of a single

event. Symptoms that were asked without reference to the mass

shooting episode, including MD and GAD symptoms, also might

have been present prior to the shooting incident. Although other

outcomes were directly in reference to the mass shooting inci-

dent, including PTSD and acute stress disorder, they too could

be influenced by preexisting psychopathology.

Three methods were used to address this issue. First, three

independent samples included both pre- and post-incident data.

The significance of pre- to post-incident changes in mental

health reached was assessed in one of these samples (Hartnett

& Skowronski, 2010). The investigators found that students’ rat-

ings of four negative moods states (depression, tension, fatigue,

and confusion) did not significantly differ between pre- and post-

incident assessment; however, they reported significantly higher

anger at the post-incident assessment. In the two other samples,

significance of changes in mental health from pre- to post-

incident was not assessed. However, descriptive data suggested

short-term increases in depression and PTSS (e.g., Littleton,

Axsom, & Grill-Taquechel, 2009; Orcutt et al., 2014).

Second, two studies assessed mental health impacts through

comparison of samples who faced different levels of exposure,

with results indicating higher symptomatology in directly

exposed subsamples. Students at Joleka High School in Fin-

land, where a shooting took place, had significantly higher

posttraumatic distress and psychiatric disturbance than students

in another city in Finland (Suomalainen et al., 2011). In the

aftermath of the 1994 Brooklyn Bridge shooting, levels of

PTSS, depression, and anxiety were higher in youth who

directly experienced the attack than an age-matched compari-

son group of youth in the same community who were not

directly exposed (Trappler & Friednman, 1996).

Finally, three studies drew on data from ongoing investiga-

tions of remote samples to assess the mental health impact of mass

shootings, as well as their broader effects on indirectly exposed

populations. For example, in the aftermath of the 1999 Columbine

massacre, researchers drew on national school-based surveys

with assessments spanning from pre- to post-incident in 1999 and

found that students’ perceptions of safety at school declined after

the attack (Addington, 2003; Brener, Simon, Anderson, Barrios,

& Small, 2002). Interestingly, students’ reports of suicidal idea-

tion and plans also significantly decreased after Columbine, per-

haps indicative some form of widespread posttraumatic growth

(e.g., increased appreciation of life), although this finding was

limited to students living in rural and suburban areas (Brener

et al., 2002). Two other investigations of remote college student

samples have shown increased fears (e.g., of walking alone, of

crime) and decreased perceived safety from pre- to post-

incident (Kaminski, Koons-Witt, Thompson, & Weiss, 2010;

Stretesky & Hogan, 2001).

Predictors of Adverse Mental Health Outcomes

Table 2 also includes significant predictors of adverse mental

health outcomes in each of the study. These predictors can be

divided roughly into three categories: (1) demographics and

pre-incident characteristics, (2) incident exposure, and (3)

post-incident functioning and psychosocial resources.

Demographic and Pre-Incident Characteristics

Demographic characteristics have frequently been included as

predictors of mental health. Most consistently, female gender

has been shown to be a predictor of post-incident psychological

adversity, associated with increased odds of PTSD (e.g., North,

Smith & Spitznagel, 1994; Suomalainen et al., 2011), higher

levels of fear (Fallahi & Lesik, 2009), and lower levels of emo-

tional and behavioral well-being (Hawdon & Ryan, 2012) in

affected samples, and higher fear in a remote sample (Vicary

& Fraley, 2010). One proposed explanation for this difference

is that women are more likely to employ a ruminative coping

style, increasing the severity and chronicity of their symptoms

(e.g., McIntyre et al., 2011; Palus, Fang, & Prawitz, 2012).

Indicators of socioeconomic disadvantage, although less

often included in post-incident studies, have also been consis-

tently associated with poor mental health. For example, in the

aftermath of the 1984 shooting at a fast food restaurant in

Lowe and Galea 75

California, higher prevalences of severe PTSD were documen-

ted among community members with lower income or who

were unemployed, relative to their counterparts (Hough et al.,

1990). Lower education was also associated with higher PTSS

among survivors of the 1992 St. Louis courthouse shooting

(Johnson et al., 2002). Among an adolescent sample, not living

with two biological parents was associated with higher psy-

chiatric disturbance (Suomalainen et al., 2011).

Other demographic characteristics have been less consis-

tently associated with post-incident mental health outcomes.

For example, younger and older age have each been associated

with adverse outcomes in both community and college student

samples (Fallahi & Lesik, 2009; Hough et al., 1990; Johnson

et al., 2002; Kaminski et al., 2010). Racial/ethnic minority

status has also been inconsistently associated with outcomes.

Two studies have found non-White race to be associated with

more severe post-incident symptoms (Fallahi & Lesik, 2009;

Kaminski et al., 2010). In contrast, among female NIU stu-

dents, African American ethnicity was associated with lower

PTSS at 2–4 weeks post-incident, whereas Asian ethnicity was

associated with higher PTSS at 8 months post-incident (Littleton,

Kumpula, & Orcutt, 2011).

Few studies have investigated whether marital and parent

status affect risk for post-incident adversity. Hough and col-

leagues (1990) found higher prevalences of severe PTSD

among widowed, divorced, or separated persons (relative to

married and single persons) and among adults with no children

at home (relative to those with 1–3 or more children); however,

the significance of these trends was not assessed. In contrast,

Johnson, North, and Smith (2002) found that being married,

relative to single or divorced, widowed, or separated, was asso-

ciated with higher PTSS.

Only one study to our knowledge has investigated the role of

genetic risk variants in predicting post-incident outcomes.

Among a subsample of NIU female students who provided

DNA samples, variants within the serotonin transporter gene

were associated with significantly greater increases in PTSS

from pre-incident to 2–4 weeks post-incident (Mercer et al.,

2012). An additional finding showing that family history of

mental illness predicted lack of recovery in MD at 3 years after

the 1991 Killeen, TX, restaurant shooting also suggests a

potential genetic contribution to post-incident responses

(North, McCutcheon, Spitznagel, & Smith, 2002).

Similarly, the results of several investigations have shown

that pre-incident psychological functioning is a strong predictor

of post-incident functioning. A retrospective assessment of

PTSD was found to predict post-incident PTSD among survivors

of the 1991 Texas restaurant shooting (Sewell, 1996). In the

aftermath of the same incident, reports of pre-incident psychia-

tric diagnosis were also associated with increased risk for PTSD

among female survivors (North et al., 1994, 1997). Among ado-

lescents exposed to the Joleka High School shooting, previous

‘‘mental support’’ from a nonguardian adult, a proxy for pre-

event functioning, was associated with increased risk for psy-

chiatric disturbance (Suomalainen et al., 2011). More recent

studies in the aftermath of college shootings have drawn on

pre-incident data and found significant associations between pre-

and post-incident assessments of mental health (e.g., Grills-

Taquechel et al., 2011; Littleton, Kumpula, et al., 2011).

A related set of findings has found that prior trauma expo-

sure increases risk for psychological adversity in the aftermath

of shooting incidents. For example, in the study of female Vir-

ginia Tech survivors, those who had experienced sexual victi-

mization prior to the event were at increased risk of PTSS

and depression 1 year after the shooting (Littleton, Grills-

Taquechel, Axsom, Bye, & Buck, 2012). Among the NIU

student sample, higher pre-incident trauma exposure was pre-

dictive of higher PTSS at two post-incident time points (Lit-

tleton, Kumpula, et al., 2011), as well as increased odds of

a nonresilient trajectory of PTSS over time (Orcutt et al.,

2014).

Incident Exposure

Indices of greater incident exposure, including proximity to an

attack, acquaintance with the deceased, and higher scores on

exposure inventories (with items assessing, e.g., seeing or hear-

ing the events and physical injuries), have consistently been

associated with more severe psychological reactions (e.g.,

Hawdon & Ryan, 2012; Littleton, Kumpula, et al., 2011;

Pynoos et al., 1987). There is some evidence that the impact

of milder forms of exposure on mental health decreases over

time. For example, in the aftermath of the NIU shooting,

moderate, severe, and extreme exposure (relative to no direct

exposure) were associated with higher PTSS 2–4 weeks post-

incident, whereas only extreme exposure was associated with

higher PTSS at 8 months post-incident (Littleton, Kumpula

et al., 2011).

In addition, emotional reactions during and after the incident

have been found to predict later psychological responses. For

example, students’ perceptions that they would be shot or were

in danger during the 1988 Illinois elementary school shooting

increased risk for PTSD (Schwarz & Kowalski, 1991a). Kum-

pula, Orcutt, Bardeen, and Varkovitzky (2011) assessed NIU

students’ experiences of peritraumatic dissociation—altered

awareness and depersonalization or derealization—during the

event and found them to be predictive of higher PTSS 2–4

weeks post-incident. Other investigators have drawn on longi-

tudinal data to show that earlier post-incident symptoms are

positively associated with symptoms at later time points (e.g.,

Bardeen, Kumpula, & Orcutt, 2013; Smith, Abeyta, Hughes,

& Jones, 2014). For example, acute stress disorder symptoms

1 week after the 1993 San Francisco office building shooting

were associated with increased odds for PTSD 7–10 months

post-incident. Being offered post-incident crisis support and

early post-incident use of mental health services have also

served as proxies of adverse initial responses, and have been

predictive of higher psychiatric symptoms later on (e.g., Mur-

tonen, Suomalainen, Haravuori, & Marttunen, 2012; North

et al., 2002). Interestingly, Murtonen, Suomalainen, Haravuori,

and Marttunen (2012) found that students’ perceptions that

early crisis support was unhelpful was also associated with

76 TRAUMA, VIOLENCE, & ABUSE 18(1)

more severe symptoms, suggesting that survivors who do not

benefit from early interventions might be at particular risk of

long-term mental health problems.

How events are perceived and remembered have also been

found to predict mental health outcomes. For example, after the

1992 St. Louis courthouse shooting, survivors’ perception that

the incident had caused them a great deal of harm, that it was

very upsetting, and that they had not recovered were each asso-

ciated with higher PTSS (Johnson et al., 2002). A small study

of school personnel in the aftermath of the 1988 Illinois ele-

mentary school shooting assessed participants’ changes in

reports of emotional, life threat, and sensory experiences dur-

ing the attack, and found that those whose reports became more

intense over time (enlargement of recall) or did not become less

intense over time (lack of diminishment of recall) tended to

have more severe symptoms (Schwarz, Kowalski, & McNally,

1993).

Other investigations have focused on indirect exposure to

events in affected and remote samples. For example, Joleka

High School students who reported higher media exposure

were at increased risk of post-incident psychiatric disturbance

(Haravuori, Suomalainen, Berg, Kiviruusu, & Marttunen,

2011). In a remote college student sample, greater exposure

to news media after the Virginia Tech shooting was associated

with significantly higher psychiatric symptoms (Fallahi, Aus-

tad, Fallon, & Leishman, 2009). Significantly higher symptoms

were also found among students who reported more time dis-

cussing the incident with family and friends, indicating that

informal conversations may serve as an additional form of indi-

rect exposure (Fallahi et al., 2009). Associations between indirect

exposure and mental health could be due in part to self-selection

and reverse causation, such that participants with more severe

symptoms might be more likely to seek out media exposure and

initiate conversations on the event. Further research employing

longitudinal and experimental designs could address these

considerations.

Post-Incident Functioning and Psychosocial Resources

As noted previously, early post-incident mental health

responses have been found to prospectively predict later post-

incident mental health responses (e.g., Bardeen et al., 2013).

In a similar vein, different classes of psychiatric symptoms

have been positively associated in cross-sectional assessments.

For example, among female survivors of the 1991 Texas res-

taurant shooting, a diagnosis of any other psychiatric disorder

was associated with increased odds of PTSD (North et al.,

1994); among the full sample, there was also significant con-

cordance between post-incident MD and PTSD. Studies have

also documented associations between post-incident fears and

PTSS in affected and remote samples (Fallahi & Lesik, 2009;

Schwarz & Kowalski, 1991a).

Research has further suggested interrelations between men-

tal and physical health problems. Higher prevalences of both

mild and severe PTSD were observed in affected community

members with fair or poor physical health, versus those with

good or excellent physical health, in the aftermath of the

1984 California fast-food restaurant shooting. Among children

directly exposed to the 1988 Illinois elementary school shoot-

ing, increased physical symptoms and visits to the school nurse

were associated with increased risk of PTSD (Schwarz &

Kowalski, 1991a). In the absence of longitudinal research, the

direction of the relationship between post-incident mental and

physical health remains unclear. Additional considerations are

whether physical health symptoms are manifestations of poor

mental health or whether preexisting physical health symptoms

or pre- to post-incident changes in physical health account for

significant associations.

In terms of psychosocial resources, research has focused on

personality characteristics, beliefs and attitudes, coping styles,

and social relationships as predictors of mental health out-

comes. Personality characteristics that have been associated

with adverse outcomes include guilt and resentment, insecur-

ity, and anxiety sensitivity (Schwarz & Kowalski, 1992a;

Stephenson, Valentiner, Kumpula, & Orcutt, 2009). Beliefs

that events are random and uncontrollable, and punitive atti-

tudes toward crime have also been associated with adverse

outcomes, whereas greater self-efficacy, sense of meaning,

spirituality and perceived benevolence of others have shown

to be protective factors (Littleton et al., 2012; Smith et al.,

2014; Vuori, Hawdon, Atte, & Räsänen, 2013).

Coping styles have been differentially associated with out-

comes. Forms of coping that involve taking action, cognitive

processing of the incident, and acceptance have been associ-

ated with lower levels of symptoms (e.g., North, Spitznagel,

& Smith, 2001; Sewell, 1996), whereas ruminative and avoi-

dant coping styles have been found to increase risk (e.g.,

Littleton et al., 2012). To some extent, means of coping in the

aftermath of an incident could represent more pervasive diffi-

culties and ways of approaching one’s experiences. In this

vein, studies drawing on pre-incident data have found those

emotion regulation difficulties and experiential avoidance,

or the tendency to disengage from difficult emotions, sensa-

tions, thoughts, and memories, to be prospective predictors

of post-incident symptoms (e.g., Bardeen et al., 2013; Kum-

pula, Orcutt, Bardeen, & Varkovitzky, 2011).

Similarly, indicators of fewer social resources (e.g., lower

perceived social support and lower social solidarity) have been

consistently associated with adverse post-incident outcomes

(e.g., Hawdon & Ryan, 2012; Littleton et al., 2012; Suomalai-

nen et al., 2011), and these differences could be driven in part

by stable personality characteristics. For example, nonsecure

attachment styles were significantly associated with higher

PTSS and lower posttraumatic growth in relationships with

others among students after a college campus shooting in Fin-

land (Turunen, Haravuori, Punamäki, Suomalainen, & Marttu-

nen, 2014).

On the other hand, researchers have been informed by Con-

servation of Resources (COR) theory (Hobfoll, 1989), which

suggests that change in psychosocial resources, rather than sta-

bility, increases risk for adverse psychological outcomes. Sup-

porting COR theory, Littleton and colleagues found that

Lowe and Galea 77

survivors’ reports of loss of life direction and pride, optimism,

and interpersonal resources (e.g., companionship) were associ-

ated with higher PTSS and psychological distress (Littleton

Axsom, et al., 2009; Littleton, Grills-Taquechel, & Axsom,

2009; Littleton, Kumpula, et al., 2011). Lower levels of

resource gain, however, were significantly associated with

higher psychological distress, suggesting that only negative

changes in resources are associated with adverse outcomes.

Processes Leading to Adverse Mental Health Outcomes

In our review, we noted findings that went beyond documenting

prevalence estimates and predictors by exploring the mechan-

isms contributing to mental health outcomes over time. A total

of seven studies (from three independent samples) did so, all

conducted within the past decade. In general, two types of

mechanisms were explored across these studies. First, studies

assessed pathways from pre-incident risk factors to post-

incident mental health through post-incident risk factors. One

example is a study in the aftermath of the NIU shooting showing

that students’ pre-incident experiential avoidance was positively

associated with their post-incident reports of peritraumatic disso-

ciative experiences, which in turn were positively associated

with PTSS (Kumpula et al., 2011). Another study of student sur-

vivors of the Virginia Tech attack found that prior sexual victi-

mization was indirectly associated with PTSS and depression

through lower self-worth, benevolence beliefs, and social sup-

port (Littleton et al., 2012).

Second, studies explored the ways in which risk factors

and mental health influence each other over time through

cross-lagged models. For example, a longitudinal study in

the aftermath of the Virginia Tech shooting found reciprocal

relationships between psychological distress and maladap-

tive coping from 2 months to 6 months, and 6 months to

1 year post-incident, suggesting that psychological distress

could perpetuate itself by undermining coping mechanisms

(Littleton, Axsom et al., 2011). This was not the case for the

model containing PTSS, wherein the paths from PTSS to

maladaptive coping reached statistical significance, but

those from maladaptive coping to PTSS did not (Littleton

et al., 2011). Another study employed cross-lagged model-

ing and found significant bidirectional relationships between

emotion regulation difficulties and PTSS from pre-incident

to 2–4 weeks after the NIU shooting, whereas only the path

from emotion regulation difficulties to PTSS was significant

from 2-4 weeks to 8 months post-incident (Bardeen et al.,

2013). For the model containing general distress, only the

path from distress to emotion regulation difficulties was sig-

nificant from pre-incident to 2—4 weeks post-incident,

whereas only the path from emotion regulation difficulties

to distress was significant from 2-4 weeks to 8 months

post-incident (Bardeen et al., 2013).

Taken together, the few studies in our review that investi-

gated mechanisms contributing to post-incident mental health

suggest a complex interplay between risk factors and outcomes

that depend in part on the timing of assessment and outcome

assessed. Further research exploring these processes will help

to establish conceptual models of pathways to post-shooting

mental health.

Discussion

The purpose of this review has been to review the extant liter-

ature on mental health in the aftermath of mass shootings. The

research to date provides evidence that these events can have

mental health consequences for victims and members of

affected communities, leading to increases in PTSS, depres-

sion, and other psychological symptoms. The few studies on

remote samples further suggest that these events can have at

least short-term psychological effects, for example, increased

fears and declines in perceived safety, on persons living far out-

side of the affected communities. These effects are not distrib-

uted equally, however, and research has identified several risk

factors for adverse outcomes, including demographic charac-

teristics (e.g., female gender and lower socioeconomic status),

higher pre-event trauma exposure and psychological symp-

toms, greater direct and indirect event exposure, and lack of

psychosocial resources (e.g., emotional regulation difficulties,

experiential avoidance, and low social support).

Although the extant body of research offers some conclu-

sions about the mental health effects of mass shootings, more

research is needed to better understand the mechanisms

through which risk and protective factors contribute to longer

term outcomes. There is a particular need for studies in the

aftermath of high-impact events. For example, we identified

no studies of affected samples in two recent events with unu-

sually high numbers of casualties—the 2012 shootings at the

Aurora movie theater and Sandy Hook elementary school.

Researchers and institutional review boards might be hesitant

to conduct studies in the aftermath of such events due to con-

cerns about retraumatizing or otherwise taking advantage of

victims. Notably, however, the majority (85%) of NIU students who completed a post-incident experimental study reported

that they would participate in the study again (Fergus, Raben-

horst, Orcutt, & Valentiner, 2011). Although a single data

source, these results suggest some evidence that study partici-

pation might not have adverse effects. Research in the after-

math of other traumatic events suggests that some persons

who have experienced trauma may actually derive benefits

from research participation (e.g., Griffin, Resick, Waldorp, &

Mechanic, 2003).

Further studies that draw on pre-incident data from ongoing

investigations would provide greater insight into the role of

pre-event functioning and trauma exposure on psychological

responses. In a similar vein, studies that include multiple waves

of follow-up data would allow for an enhanced understanding

of longitudinal patterns of responses and the processes that lead

to chronic symptoms. The research could also be enriched by

further studies that include positive outcomes (e.g., resilience

and posttraumatic growth) and incorporate additional sources

of data, including genetic variants and information on commu-

nity characteristics and resources. In addition to further

78 TRAUMA, VIOLENCE, & ABUSE 18(1)

research on affected samples, more investigations are needed to

understand the broader impact of mass shootings on unaffected

communities. It was notable that only 5 of the 28 identified

samples focused on remote populations; as such, our conclu-

sions regarding the widespread mental health effects of mass

shootings are tentative at best.

Additional research would also inform interventions to pre-

vent and treat post-incident mental health problems. The first

step in prevention would be to decrease the likelihood that mass

shooting events occur in the first place. The rarity of these

events precludes the use of statistical modeling to predict their

occurrence (Swanson, 2011). Researchers have accordingly

advised against the use of risk profiles, which have the poten-

tial for false positives bias, and stigmatization (Reddy et al.,

2001). Instead, a deductive threat assessment approach in

which a team of professionals gathers information about a par-

ticular case to assess the likelihood that a violent episode will

occur, and formulates a response based on that assessment,

have been proposed (e.g., Cornell & Allen, 2011; Reddy

et al., 2011). Others have suggested the need for promoting

positive school climates in which there is open dialogue

between students, teachers, and administrators to reduce the

likelihood of school shootings (Mulvey & Cauffman, 2001),

and efforts to improve access to and continuity of high-

quality mental health services for people with serious mental

illness to prevent violent behaviors among this group (Swanson,

2011). Finally, others have noted the high rates of gun ownership

and firearm mortalities in the United States compared to those in

other developed countries as evidence of the need for a range of

efforts to reduce gun access (e.g., Shultz, Cohen, Muschert, &

Flores de Apodaca, 2013). An observational study showing

declines in firearm-related deaths, suicides and homicides, and

a complete absence of mass shooting episodes, in Australia a

decade after gun law reforms aiming to limit civilian access

to semiautomatic and pump-action shotguns and rifles pro-

vides support for such efforts (Chapman, Alpers, Agho, &

Jones, 2006).

In addition to preventing mass shootings, it would be impor-

tant to develop interventions to address mental health problems

in their wake. Trained crisis response teams that establish

safety, evaluate the psychological needs of victims, connect

survivors with a range of services to meet their needs, and eval-

uate response efforts have been proposed to mitigate the effects

of school violence (Crepeau-Hobson, Sievering, Armstrong, &

Stonis, 2012). Hobfoll and colleagues (2007) have also identi-

fied five empirically supported principles for mental health

responses to mass trauma—promoting a sense of safety, calm-

ing, a sense of self- and community-efficacy, connectedness,

and hope.

The empirical research also lends support for approaches

that identify survivors most at risk of adverse outcomes, includ-

ing women, persons of lower socioeconomic status, those who

faced higher levels of exposure, and persons lacking strong

social support networks. Furthermore, extant studies suggest

interventions that enhance emotion regulation and active cop-

ing skills and that encourage engagement with and acceptance

of emotions, thoughts, memories, and sensory experiences

(e.g., Metz et al., 2013). These skill-building interventions

could be part of the standard curriculum and could promote

resilience after a range of traumatic events and stressors.

The recommendations for future research, policy, and prac-

tice are made with caution, given the limitations of this review.

For example, although our efforts to identify studies meeting

our inclusion criteria were exhaustive, we did not track such

data as the total number of articles identified across all of

our searches, and the number that were dropped based on

each criterion. In addition, although the first author checked

and rechecked coding for accuracy, articles were not double-

coded, and a system for establishing the reliability of the article

screening and coding process was not developed and applied.

Taken together, these limitations suggest a need for a more sys-

tematic review, particularly as additional literature on this topic

is published. Further reviews could also apply broader inclu-

sion criteria, for example, to provide insight into the influence

of direct and indirect exposure to mass shootings on other

domains of functioning (e.g., physical health and social func-

tioning). Inclusion of non-English language articles could shed

additional light on the influence of mass shootings on mental

health cross-culturally. Qualitative studies could also be inte-

grated to provide a richer sense of the patterns and predictors

of mental health in the aftermath of shootings. Our review of

predictors also focused on factors that account for significant

variation in post-shooting mental health within each study, and

we did not attend to potential between-study sources of varia-

tion, such as differences in samples (e.g., age-group and extent

of exposure), procedures (e.g., timing of assessment), and event

characteristics (e.g., single vs. multiple shooters, number of

injuries and fatalities). Future research could examine within- and

between-study variability simultaneously using meta-analytic

techniques. Finally, we did not compare the prevalence esti-

mates and predictors of mental health outcomes in the after-

math of mass shootings to those in the aftermath of other

traumatic events. Inclusion of mass shootings on trauma inven-

tories in future epidemiological studies would provide insight

into this issue.

In summary, the limited research suggests that mass shoot-

ing incidents can lead to an array of mental health problems in

survivors and members of affected communities. Furthermore,

they have been associated with increased fears and decreased

perceptions of safety in indirectly exposed populations. A vari-

ety of risk and protective factors have been identified, includ-

ing demographic characteristics, pre-event trauma exposure

and functioning, event exposure, and psychosocial resources.

Further research that explores the processes contributing to

long-term psychological responses will yield important impli-

cations for post-incident interventions to reduce mental health

impacts.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect

to the research, authorship, and/or publication of this article.

Lowe and Galea 79

Funding

The author(s) received no financial support for the research, author-

ship, and/or publication of this article.

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