Increasing Cognitive Readiness Through Computer and Videogame–Based Training

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Article

Increasing Cognitive Readiness Through Computer and Videogame–Based Training

Jorge Peña1 and Nicholas Brody2

AbstractIn order to examine the cognitive readiness effects of training technologies, 123 participants watched emotional or tactical military training videos and then played a training videogame in a pre-post test between-subjects experiment. Emotional training video exposure reduced participants’ ability to suppress emotion and need to control one’s thoughts. After playing the videogame, participants exposed to the emotional video had higher metacognitive self-consciousness scores. Nationalism was negatively associated with emotion reappraisal for participants exposed to the emotional training video. However, patriotism was linked to higher emotion suppression scores. The results illustrate how media priming connects to short-term cognitive readiness outcomes and how trainee nationalism and patriotism modulate exposure effects.

Keywordsmedia priming, social identification, interactive military training, cognitive readiness, emotion regulation

New technologies are often created to prepare people to more effectively perform their jobs (e.g., training videos, simulators, etc.), and much research is conducted to evalu-ate the effectiveness of such technologies (Graesser & King, 2008). The results of such inquiries have practical value and can also inform media effects theories. In particular,

1University of California, Davis, USA2University of Puget Sound, Tacoma, WA, USA

Corresponding Author:Jorge Peña, Department of Communication, University of California, Davis, 367 Kerr Hall, Davis, CA 95616, USA. Email: [email protected]

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2 Communication Research

this study examines the impact of mediated military training. Building upon media priming perspectives, exposure to videos and videogames is expected to trigger inter-linked memories that turn into cognitions, emotions, and behaviors (Roskos-Ewoldsen, Roskos-Ewoldsen, & Dillman Carpentier, 2009). The study also incorporates social identity approaches predicting that the same media experience has different outcomes to the extent that media exposure activates group prototypes and norms on perceivers (Hogg & Reid, 2006). We discuss an experiment testing whether exposure to emo-tional or tactical military training videos influences two components of cognitive readiness, emotional regulation and metacognition. We also examine how social iden-tification factors such as individuals’ nationalism and patriotism relate to emotional regulation and metacognition.

Training for Cognitive ReadinessSuccess in modern military situations depends on cognitive readiness (Simpson & Oser, 2003). Cognitive readiness refers to individuals’ mental preparation to engage in military actions (Morrison & Fletcher, 2002). Cognitive readiness is composed of situ-ation awareness, memory, transfer of training, metacognition, automaticity, problem solving, decision making, mental flexibility/creativity, leadership, and emotional regu-lation (see Morrison & Fletcher, 2002).

U.S. military forces attempt to increase the cognitive readiness of personnel by means of computer training systems. Training technologies offer advantages such as increased safety, repeated expert advice, and lower costs (Simpson & Oser, 2003). However, there are unanswered questions regarding the effectiveness of military train-ing technologies (Graesser & King, 2008). According to Graesser and King (2008), it is vital to test the learning outcomes of military training technologies using controlled experiments as available studies show mixed results.

Readiness training is often accomplished by developing either emotion control or tactical skills that are appropriate to military contexts (Morrison & Fletcher, 2002). When conducting emotion control training, a video may expose personnel to an emo-tional military scenario and have them identify and develop responses that would miti-gate intense emotional distress (i.e., “How would you calm down your platoon and mourn if a squad mate was killed?”). When conducting tactical skill training, a video may expose trainees to a scenario in which contextual information is ambiguous and has them state their selected response (i.e., “Would you shoot an ambiguous, not fully identified civilian target?”). This training approach assumes that the most effective way to deal with combat situations is to highlight ambiguous cues and to make person-nel aware of effective tactical reactions to them. This approach highlights dilemmas faced in combat and requires personnel to consider likely tactical responses but does not highlight emotions. Combat can involve encounters that evoke strong emotional responses such as anger and fear, and these emotions may prompt impulsive aggres-sion against targets that are not threatening. Indeed, at high levels of intensity, emo-tions can overpower cognitive processing and deliberative action (Loewenstein & Lerner, 2003). To prevent such outcomes, readiness training may attempt to enhance the emotional regulation and metacognitive components of cognitive readiness.



Peña and Brody 3

Emotion regulation refers to trying to influence which emotions we experience, when we have them, and how emotions are expressed (Gross & John, 2003). Metacognition refers to control, modification, and interpretation of worrying thoughts (Cartwright-Hatton & Wells, 1997). By exposing trainees to emotionally intense scenarios and identifying ways to respond to their influence, individuals may learn to regulate their intense emotions and more deliberately consider alternative actions when they encoun-ter similar situations. In addition, training to cope with negative emotions and unwanted thoughts is important for people in high-pressure jobs (e.g., police officers), and vir-tual training can affect emotion regulation strategies and reduce emotional intensity (Bosse, Gerritsen, de Man, & Treur, 2012).

Unfortunately, theory and research does not adequately inform the design and eval-uation of emotion and tactical-based training technologies. Additionally, although scholars outline the theoretical mechanisms related to cognitive readiness outcomes, they do not present empirical evidence linked to the proposed theoretical constructs. For example, Grier (2012) suggests but does not verify the assumption that cognitive readiness is related to trainee motivation, knowledge, and expertise. Also, though Morrison and Fletcher (2002) discuss how computer-based instruction and simula-tions can improve cognitive readiness, they do not theorize exactly how these tech-nologies affect trainee cognition, emotion, and behavior. Considering this, the present study assumes that cognitive readiness factors such as emotion regulation and meta-cognition are a product of media experiences. For instance, increased metacognitive outcomes reveal vigilance, conscious awareness, and attentive involvement when learning from TV content (see Salomon, 1983). Additionally, we explore the assump-tion that media exposure activates emotional responses that can transfer to subsequent decisions and perceptions (Goldberg, Lerner, & Tetlock, 1999; Nabi, 2003a), and how this process affects emotional regulation outcomes. These assumptions resonate with media priming research and its interest in how exposure to TV shows and videos influ-ences ensuing cognitive and affective processes.

Media PrimingMedia priming refers to the effect of exposure to media content on subsequent judg-ments and behaviors (Roskos-Ewoldsen et al., 2009) and this research is concerned with how prior media events unconsciously affect individuals’ short- and long-term responses. Media exposure is theorized to bring specific thoughts and emotions into focal awareness, and the activation of such cognitive and affective structures can auto-matically steer ensuing judgments and behaviors (Berkowitz, 1984). For example, exposure to violent TV programs and violent videogames can lead to aggressive cog-nition and behavior, especially when participants are frustrated or possess aggressive traits (Bushman & Anderson, 2002). Media priming can also shift people’s foci of attention and evaluation standards. Exposure to music videos depicting stereotypical gender roles results in carryover effects including stereotypical judgments of a woman depicted in a later recording (Hansen & Krygowski, 1994). Repeated media priming episodes can lead to long-term effects. For instance, playing violent videogames fre-quently may increase the accessibility of violent thoughts and also modify moral




judgments (Vieira & Krcmar, 2011), along with contributing to the development of aggressive personality (Bushman & Anderson, 2002). Longitudinal effects are also likely as repeated exposure to media content cultivates media-congruent attitudes (Gerbner, Gross, Morgan, Signorielli, & Shanahan, 2002).

The research above has repercussions for the predicted effects of emotional control and tactical training. Although intended to stimulate emotional regulation and meta-cognition, emotion-based training may initially prime negative emotions rather than helping trainees learn how to regulate them (at least in the short term and before train-ees learn to master emotional and metacognitive responses). Before trainees discover how to control their reactions, training videos’ focus on negative emotional events (e.g., the death of a comrade) may distract attention from ambiguous contextual cues and they may also become more aggressive. For example, after watching an anger-inducing video showing clear wrongdoing, participants believing that a perpetrator went unpunished were harsher against other wrongdoers compared with those who were uncertain about punishment and those thinking that the crime was punished (Goldberg et al., 1999). Also, negative emotions can signal that accessible thoughts are not valuable, and thus discourage metacognition (Clore & Huntsinger, 2007). However, tactical training does not focus on emotional situations and negative emotions and, thus, should afford more emotional regulation and metacognition.

Hence, we propose the following hypothesis:

Hypothesis 1 (H1): Exposure to an emotional training video will reduce emotion regulation and metacognition scores compared with exposure to a tactical video.

An important component of training is the degree to which training transfers to new situations (Morrison & Fletcher, 2002). In this study, we look at two forms of transfer effects: First, the degree to which immediate changes in emotional regulation and metacognition remain apparent in new situations, and second, behavioral transfer reflecting whether training influences subsequent responses. For example, people using training simulators can decide what course of action they will implement and, according to media priming mechanisms, these choices will reflect information that people were previously exposed to. Based on media priming assumptions, we predict that information presented in the training videos will transfer into different in-game behaviors. Specifically, a tactical training video reminding trainees not to open fire unless there is an imminent threat may transfer into opening fire less frequently when subsequently interacting in a new training situation. Thus, we propose Hypothesis 2:

Hypothesis 2 (H2): Exposure to an emotional training video will exert transfer effects (i.e., reduced emotion regulation and metacognition, and greater aggressive-ness) in new situations compared with the tactical video.

Social IdentityBoth nationalism and patriotism represent identification with a country (Federico, Golec, & Dial, 2005). However, nationalism denotes affinity with a nation coupled



Peña and Brody 5

with enmity toward other countries (Federico et al., 2005). Patriotism refers to a strong identification with a nation without hostility to other countries (Federico et al., 2005). These factors are often studied from the outlook of social identity theory (SIT) and self-categorization theory (SCT; Huddy & Khatib, 2007). SIT refers to people’s attach-ment to in-groups and its effects on self-esteem, perceptions, and behavior (Hogg & Reid, 2006). SCT focuses on cognitive processes related to following prototypes and group norms (Hogg & Reid, 2006). These factors relate to SIT and SCT in that both nationalistic and patriotic individuals show positive in-group identification. However, nationalistic individuals show negative out-group identification (Federico et al., 2005).

A promising social identity research area examines how the same media experience produces different outcomes to the extent that media exposure activates group norms and prototypical behaviors (Hogg & Reid, 2006). For instance, exposure to TV story-lines depicting Latinos led to lower attributions of the main character’s qualifications when viewers identified more with their own race and the storyline was ambiguous (Mastro, Behm-Morawitz, & Kopacz, 2008). Consistent with gender norms and proto-types, men expected women to be more repulsed by adult media content than them-selves while women estimated men to be more aroused than they did (Reid, Byrne, Brundidge, Shoham, & Marlow, 2007).

However, predicting cognitive readiness outcomes based on nationalism and patri-otism scores is not a straightforward affair. Patriotism is positively related to enroll-ment in the U.S. Army, and more patriotic personnel perform more effectively (Burk & Faris, 1982). Patriotism is also predicted to affect trainee stress management out-comes and encourage perseverance (Cigrang, Todd, & Carbone, 2000). In addition, patriotism and nationalism are positively related to National Guard soldiers’ mission readiness and intention to remain in the military (Griffith, 2010). Also, nationalism and patriotism are positively correlated with more hawkish foreign-policy attitudes and increased support for military action (Federico et al., 2005). In contrast, national-ism and patriotism are negatively related to critical thinking skills (Williams, Foster, & Krohn, 2008), along with reduced political knowledge and student grade point aver-age (GPA) scores (Schatz, Staub, & Lavine, 1999). Critical thinking skills, knowledge, and learning performance are all key factors in the context of training technologies. Thus, it could be expected that training video exposure could result in subsequent effects on trainees with different nationalistic and patriotic attitudes. For instance, training videos could surprise or challenge the expectations of trainees with more nationalistic attitudes. This in turn could trigger increased attempts to control cogni-tions and emotions. Additionally, training videos dealing with a comrade’s death may upset both nationalistic and patriotic participants and, thus, prompt increased meta-cognition and emotion regulation. Because training video exposure could lead to either increased or decreased cognitive readiness effects depending on trainees’ nationalistic and patriotic views, the first research question thus asks:

Research Question 1 (RQ1): What are the effects of nationalism and patriotism on emotion regulation, metacognition, and in-game behavior after exposure to the training videos and playing a training videogame?




Method

OverviewParticipants completed an online survey measuring the cognitive readiness factors out-lined by Morrison and Fletcher (2002, see below), and then signed up for an experi-mental session. Participants were randomly assigned using a research randomizer website. They were assigned to view one of two military training videos similar in length and production style but featuring different content. The participants viewed either video only once. One training video depicted an emotional military scenario (i.e., “How would you calm down your platoon and mourn if a squad mate was killed?”) and another a tactical military scenario (i.e., “Would you shoot an ambigu-ous, not fully identified target?”). Participants then completed the cognitive readiness survey a second time before playing “Moral Combat,” a military training computer game developed by Center for the Army Profession and Ethic (CAPE, 2013). Participants completed the cognitive readiness survey for the third time after playing the game mission. The study took about 1 hour.

ParticipantsOne hundred twenty-three students from a U.S. university participated in the study in exchange for course credit. The average age of participants was 20.62 years (SD = 3.05); 83 participants were women. Participants had 12.75 years of computer experi-ence (SD = 2.57) and 7.94 years of videogame experience (SD = 5.95). Most partici-pants were Caucasian (56.1%), followed by Asian (17.9%), Hispanic (14.6%), African American (4.9%), and of Other (6.5%) ethnic origin. Few participants were members of Reserve Officers’ Training Corps (ROTC; 3.3%) or came from military families (5.7%). Six participants were removed from the analysis based on the awareness check below.

ProcedureParticipants completed an initial online survey asking for demographic information including age, sex, ethnicity, computer and videogame experience, whether they were part of ROTC, or whether they had family members in the military. They also com-pleted baseline cognitive readiness scales a week before exposure to military training videos and playing the training videogame. After the survey, the participants selected a time to come to the lab. Individuals were assigned to a computer terminal upon arrival to the lab.

Once they were seated at the computer, participants viewed one of the two training videos and then completed the cognitive readiness questionnaire for a second time. After completing the survey, the participants played a mission in the training video-game. The game mission featured a training module and then the mission itself. The game training module taught users how to move their character, shoot a gun, and take photos.



Peña and Brody 7

Following the game training module, participants began the training videogame mission. “Moral Combat” is a first-person shooter-like videogame sponsored by CAPE (2013). “Moral Combat” runs on the America’s Army videogame engine, and it does so on Windows machines. The program introduces ethical dilemmas that are expected to prompt discussion among soldiers regarding their decisions. The training game is recommended for use at platoon and squad levels (CAPE, 2013). To play “Moral Combat,” participants needed to go through a training session depicting an U.S. Army boot camp. Participants trained for 7 minutes on how to move, aim, shoot, take pictures, and make in-game decisions. The game mission itself lasted 6 minutes, and participants needed to take pictures of targets in a bazaar, operate when under enemy fire, interrogate suspects, and inspect a room either forcefully or defensively.

Participants were assigned as the leader of a squad of nine soldiers. The mission required participants to walk through a small town in a fictional middle-eastern coun-try and take photos of merchants, vehicles, and other areas marked within the game. A pre-scripted event in the game resulted in shots being fired at the participant’s squad from a building after about 2 minutes of taking photos. At this point, participants were tasked with making several split-second decisions (e.g., returning or ceasing fire). Ultimately, participants were instructed to enter the building with their squad mates and then locate the enemy. Participants also made immediate decisions when inside the building (e.g., a violent or proper interrogation, entering a room using lethal or non-lethal force). The mission was completed upon entering the final room in the building. After playing the game once, the participants completed the survey for the third time.

Independent VariablesMilitary training videos. The videos were part of the “Leader Challenge” training pro-gram (Praevius Group, 2012). Leader challenge is a web-based training system designed to increase U.S. Army cadets’ cognitive readiness before deployment. The training program contains video recordings selected from more than 500 interviews depicting personal accounts of leader behaviors in critical incidents in Iraq and Afghanistan (Miller, Self, & Garven, 2009). The videos also consider the insights derived from interviews, surveys, and checklists of common types of experiences identified by leaders trained at West Point, along with information compiled from Army Internet forums and interviews with officers and platoon leaders (Miller et al., 2009). According to Miller et al. (2009), content selection for the leader challenge videos considered personal experiences that were not well supported in formal training and that had a considerable decision component (e.g., opening vs. holding fire, dealing with casualties). Thus, the videos depict practical problems that have multiple solutions.

After viewing all 19 training videos, the authors identified two videos similar in length and style but different in content. The video titled “Shoot/Don’t Shoot” was more tactical in nature, as it depicted a platoon leader finding a dead body and spotting someone ostensibly videotaping the scene. Cadets need to decide whether they would




shoot the suspect based on rules of engagement or whether they would hold their fire until identifying the suspect. The suspect turned out to be a boy playing with a toy. The success criteria were tactical as trainees needed to identify whether someone was film-ing, reducing collateral damage, securing the area, and communicating with adjacent units. The video lasted 4 minutes and 25 seconds.

The video titled “Recoil” recounts the death of a U.S. Army Private by sniper fire. The unit is angry and the platoon leader needs to address unit morale while keeping focus on the mission. The success criteria included listening personally by showing openness and availability, monitoring for issues, facilitating the mourning process, sending letters home, reinforcing mission focus, and using available resources includ-ing chaplains, leaders, and support teams. This video had strong emotional compo-nents. The manipulation check below confirmed that the videos activated emotions that matched their content on participants. This video lasted 4 minutes and 21 seconds.

Nationalism and patriotism. Federico et al.’s (2005) scale assessed nationalism and patriotism, and was applied in an online survey prior to arriving in the lab. Examples of nationalism items were “The more the United States actively influences other coun-tries, the better off these countries will be” and “To maintain our country’s superiority, war is sometimes necessary”; examples of patriotism items were “I am proud to be an American” and “I have great love for my country.” The nationalism and patriotism scales had five items each, formulated on a Likert-type scale from 1 (strongly dis-agree) to 7 (strongly agree). Reliability was good (α = .82). Principal components analysis with a varimax rotation and a forced two-factor solution showed that factor loadings ranged from .62 to .89 for patriotism, and .54 to .66 for nationalism. No items cross-loaded above a .33 level. The two factors accounted for 56% of the variance.

Dependent VariablesParticipants completed self-report measures at three points throughout the study: (1) in an online survey prior to arriving in the lab, (2) after viewing either the tactical or emotional training videos, and (3) after completing the training videogame scenario. All scales were presented randomly to minimize order effects. Several other cognitive readiness factors will appear in a separate study. Descriptive statistics and intercorrela-tions appear in Table 1.

Metacognition scales. Metacognition was measured with Cartwright-Hatton and Wells’s (1997) cognitive self-consciousness and need to control thoughts metacognition sub-scales. Participants rated their agreement with the items on a 4-point Likert-type scale (1 = strongly disagree, 4 = strongly agree). The cognitive self-consciousness scale consisted of six items (i.e., “I am constantly aware of my thinking,” “I am aware of the way my mind works when I am thinking through a problem”). Reliability was good (α = .88). The need to control thoughts scale also had six items (i.e., “Not being able to control my thoughts is a sign of weakness,” “It is bad to think certain thoughts”).



9

Tab

le 1

. M

eans

, Sta

ndar

d D

evia

tions

, and

Cor

rela

tions

Am

ong

Stud

y Va

riab

les

(N =

117

).

M (S

D)

Emot

ion

RE 1

Emot

ion

SUP

1M

etac

ogni

tion

CSC

1M

etac

ogni

tion

NC

T1Em

otio

n RE

2Em

otio

n SU

P 2

Met

acog

nitio

n C

SC 2

Met

acog

nitio

n N

CT

2Em

otio

n RE

3Em

otio

n SU

P 3

Met

acog

nitio

n C

SC 3

Met

acog

nitio

n N

CT

3N

atio

nalis

mPa

trio

tism

Rifle

sh

ots

Emot

ion

RE 1

5.26

(0.8

1)—

Em

otio

n SU

P 1

3.43

(1.2

6)−.

04—

M

etac

ogni

tion

CSC

12.

96 (0

.52)

.14

−.05

—

Met

acog

nitio

n N

CT

12.

29 (0

.44)

.10

.13

.09

—

Emot

ion

RE 2

5.37

(0.7

8).6

9***

−.04

.04

.19*

—

Emot

ion

SUP

23.

41 (1

.23)

−.06

.75*

**.0

04.2

0*.0

8—

M

etac

ogni

tion

CSC

12.

95 (0

.51)

.03

−.07

.69*

**.1

8†.0

2−.

02—

M

etac

ogni

tion

NC

T 2

2.30

(0.4

1).0

8.0

9−.

05.6

8***

.17†

.16†

.15

—

Emot

ion

RE 3

5.32

(0.8

7).5

9***

−.14

.04

.10

.80*

**.0

2.1

4.0

8—

Em

otio

n SU

P 3

3.35

(1.4

1)−.

05.7

2***

−.03

.13

.07

.91*

**−.

01.1

6−.

02—

M

etac

ogni

tion

CSC

32.

87 (0

.56)

−.00

3−.

09.6

0***

.07

.04

−.01

.83*

**.0

8.1

9*.0

4—

M

etac

ogni

tion

NC

T 3

2.28

(0.4

9).0

4.1

4−.

09.5

4***

.14

.15

.07

.77*

**.0

5.2

1*.1

0—

N

atio

nalis

m3.

66 (0

.94)

−.06

−.00

1−.

123

.003

−.08

−.05

−.08

.02

.04

−.05

−.04

.03

—

Patr

iotis

m5.

14 (1

.20)

.13

−.05

−.11

−.18

*.0

1.0

2−.

09−.

14.0

2.0

5−.

03−.

13.4

0***

—

Rifle

sho

ts2.

31 (5

.57)

.01

−.02

.03

−.12

−.11

−.03

−.14

−.02

−.15

−.01

−.12

.01

.03

.07

—Vi

deo

0.08

(1.0

0)−.

10.1

0−.

03.0

5−.

02.2

0*−.

14.1

8*−.

10.1

5†−.

16†

.09

.07

−.04

.18†

Not

e. R

E =

reap

prai

sal;

SUP

= su

ppre

ssio

n; C

SC =

cog

nitiv

e se

lf-co

nsci

ousn

ess;

NC

T =

need

to c

ontr

ol th

ough

ts; V

ideo

= v

ideo

con

ditio

n (−

1 =

emot

iona

l, 1

= ta

ctic

al);

1 =

pre-

vide

o;

2 =

afte

r vi

deo;

3 =

afte

r ga

me.

† p <

.10.

*p

< .0

5. *

*p <

.01.

***

p <

.001

.




Reliability was α = .67. The items loaded into the expected two main factors that explained most of the variance. When present, a three-factor solution comprised a third factor based on a single item and with eigenvalues that were marginally above 1 (i.e., 1.11 and 1.16). Thus, the two-factor solution was preferred because it explained most of the variance and was also expected by theory (Cartwright-Hatton & Wells, 1997).

Emotion regulation and suppression scales. Emotion regulation was measured with Gross and John’s (2003) emotion suppression and emotion reappraisal scales (1 = strongly disagree, 7 = strongly agree). The emotion suppression scale consisted of four items (i.e., “I control my emotions by not expressing them,” “I keep my emotions to myself”). Reliability for the emotion suppression scale was good (α = .86). The emo-tion reappraisal scale consisted of six items (i.e., “When I want to feel less negative emotion, I change the way I’m thinking about the situation,” “When I’m faced with a stressful situation, I make myself think about it in a way that helps me stay calm”). Reliability for the emotion reappraisal scale was also good (α = .84). A factor analysis indicated that the emotion reappraisal and suppression items loaded into the two expected factors described by Gross and John (2003). The two scales loaded into three factors only in the online survey prior to coming to the laboratory. However, the third factor had an eigenvalue of 1.04 and, additionally, comprised a single item. Factor loadings ranged from .52 to .84 for reappraisal, and .81 to .90 for suppression. No items cross-loaded above a .15 level. The two factors accounted for 57% of the vari-ance. Thus, we retained the expected two-factor emotion reappraisal and suppression solution.

Number of rifle shots. Behavioral transfer effects were operationalized as the influence of exposure to the training videos on the numbers of shots fired in the training video-game mission. Participants did not need to open fire during the videogame mission. However, they could open fire while playing the mission. Two independent coders counted the number of rifle shots. The coders were in high agreement (r = .93, p = .001). Participants fired 2.31 shots in average (SD = 5.57). Three participants were extreme outliers because they fired more than 20 shots and were removed from the analysis. Six sessions were not coded due to recording issues.

Results

Awareness and Manipulation ChecksAfter completing the experiment, the participants were questioned about their aware-ness of the aims of the study using funneled debriefing forms. Six participants showed high awareness of the aims of the study. These participants were excluded from the analysis because this study explores unconscious priming and transfer effects on cog-nitive readiness.

To ensure that the training videos activated emotions that related to the expected focus of the training videos, individuals responded to an open-ended question



Peña and Brody 11

inquiring about what they thought about the randomly assigned training video (i.e., “Did you notice any particular pattern or theme in the video depicting the soldier’s story?”). The words individuals used to describe their experience were analyzed with the Linguistic Inquiry and Word Count program (LIWC; Pennebaker, Booth, & Francis, 2007). LIWC uses a pre-validated dictionary to categorize the words of a given text. Participants assigned to the emotional video that depicted bereaving a U.S. soldier were expected to use more emotion-related words, especially negative emotion words.

A one-way analysis of variance (ANOVA) examined the effect of video condition on the resulting word categories. Individuals in the emotional video condition used more negative emotion words (e.g., hurt, nasty) than those in the tactical video condi-tion, F(1, 123) = 13.01, p < .01, η2 = .10. Participants in the emotional video condition also used more affect words (e.g., cried, sad) than those in the tactical video condition, F(1, 123) = 7.62, p < .01, η2 = .06. Individuals in the emotional video condition also used more words related to death (e.g., bury, kill) than those in the tactical video con-dition, F(1, 123) = 7.52, p < .01, η2 = .06. Finally, participants in the emotional video condition used more social words (e.g., talk, friend) than those in the tactical video condition, F(1, 123) = 16.25, p < .001, η2 = .12. In conclusion, the training video manipulation operated in full force.

Cognitive Readiness Effects of Exposure to Training VideosH1 predicted that exposure to the emotion-based training video would reduce emo-tional regulation and metacognition relative to exposure to the tactical video. The results were analyzed with a series of hierarchical multiple regressions. The video exposure condition variable was effects coded (tactical video = 1; emotional video = −1), and the nationalism and patriotism factors were centered. The pre-experiment online survey measurement of each dependent variable was entered in the first block to control for the baseline level of each variable. Participant gender was not signifi-cantly related to any of the dependent variables, and so it was not included as a control variable. The effects-coded video exposure condition variable and the centered nation-alism and patriotism factors were entered in the second block. Multiplying the condi-tion variable by the centered nationalism and patriotism factors created two interaction terms. The interaction terms were entered in the third block. Tolerance (TOL) and variance inflation factor (VIF) tests showed no collinearity between the predictor vari-ables for each regression.

Emotion regulation. Table 2 displays the results for emotion suppression and reap-praisal after exposure to the training videos. The overall F tests indicated that the models significantly predicted emotion reappraisal and suppression. The video condi-tion was related to emotion suppression after training video exposure, even after con-trolling for self-reported emotion suppression from the initial online survey. Thus, individuals who viewed the emotional video reported lower emotion suppression than those who viewed the tactical video. The videos did not impact emotion reappraisal.




Table 3. Hierarchical Regressions Predicting Metacognition After Exposure to the Training Videos (N = 117).

Metacognition cognitive self-consciousness

Metacognition need to control thoughts

Predictor variables B SE B B ∆R2 B SE B B ∆R2

Step 1: Metacognition at baseline survey

.69 .07 .69*** .48*** .63 .06 .68*** .46**

Step 2: Video condition −.07 .04 −.13† .02 .06 .03 .15* .02†

Patriotism −.02 .03 −.04 −.002 .03 −.01 Nationalism .03 .04 .05 −.002 .03 −.004 Step 3: Interaction between

Patriotism and Video condition−.04 .03 −.09 .01 −.03 .03 −.09 .01

Interaction between Nationalism and Video condition

.06 .04 .11 .02 .03 .05

Note. Cognitive self-consciousness: total R2 = .48; adjusted R2 = .48. F(6, 116) = 19.12, p < .001. Need to control thoughts: total R2 = .49; adjusted R2 = .46. F(6, 116) = 17.57, p < .001.†p < .10. *p < .05. **p < .01. ***p < .001.

Metacognition. Table 3 displays the regressions for metacognition cognitive self-con-sciousness and metacognition need to control thoughts scores after exposure to the training videos. Participants exposed to the emotional video reported less of a need to control their thoughts and suppress emotions compared with those exposed to the tac-tical video. Video exposure did not affect metacognition need to control thoughts scores.

Table 2. Hierarchical Regressions Predicting Emotion Regulation After Exposure to the Training Videos (N = 117).

Emotion suppression Emotion reappraisal


Step 1: Emotion regulation at baseline survey

.73 .06 .75*** .57*** .67 .07 .69*** .48**

Step 2: Video condition .19 .08 .15* .03* .04 .05 .06 .01Patriotism .11 .07 .11† −.05 .05 −.07 Nationalism −.15 .09 −.12† −.02 .06 −.03 Step 3: Interaction between



−.03 .09 −.02 −.05 .06 −.05

Note. Suppression: total R2 = .60; adjusted R2 = .58. F(6, 116) = 27.29, p < .001. Reappraisal: total R2 = .49; adjusted R2 = .46. F(6, 116) = 17.40, p < .001.†p < .10. *p < .05. **p < .01. ***p < .001.



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Thus, H1 was partially supported. Video exposure had reliable short-term effects on two out of four subcomponents of cognitive readiness. Individuals who viewed the emotional video reported lower emotion suppression scores than those who viewed the tactical video. In addition, participants exposed to the emotional video had lower metacognition need to control thoughts scores compared with those exposed to the tactical video. No other significant effects were found, though a near-significant effect implied that individuals who viewed the emotional training video reported higher cog-nitive self-consciousness scores than those who viewed the tactical video. We refrained from highlighting near-significant effects but, as shown below, this pattern achieved statistical significance after playing the military training videogame.

Cognitive Readiness Effects After Playing a Military Training VideogameH2 predicted that the emotional training video would exert transfer effects (reduced emotion regulation and metacognition, and greater aggressiveness) in new situations compared with the tactical video. RQ1 examined nationalism and patriotism effects on cognitive readiness outcomes. The results were examined with hierarchical multiple regressions controlling for emotion regulation and metacognition scores prior to the training videos.

Emotion regulation. Table 4 displays the results for participants’ emotion suppression and emotion reappraisal scores collected after participants played the videogame train-ing mission. For emotion suppression, the overall model was significant. The control variable of emotion suppression at the initial baseline survey significantly predicted emotion suppression after playing the videogame. However, there was no support for

Table 4. Hierarchical Regressions Predicting Emotion Regulation After Playing a Videogame Mission (N = 117).

Emotion suppression Emotion reappraisal


Step 1: Emotion regulation at baseline survey

.81 .07 .72*** .52*** .64 .08 .59*** .35**

Step 2: Video condition .16 .09 .11† .03† −.06 .07 −.07 .02Patriotism .17 .08 .15* −.09 .06 −.12 Nationalism −.20 .11 −.13† .13 .08 .14† Step 3: Interaction between

Patriotism and Video condition−.08 .08 −.07 .004 .02 .06 .03 .03*


.06 .11 .04 .16 .08 .17*

Note. Suppression: total R2 = .52; adjusted R2 = .52. F(6, 116) = 21.32, p < .001. Reappraisal: total R2 = .41; adjusted R2 = .38. F(6, 116) = 12.65, p < .001.†p < .10. *p < .05. **p < .01. ***p < .001.




Figure 1. Interaction effect between emotional and tactical training video exposure and nationalism scores.

H2 as training video exposure was not significantly related to either measure of emo-tional regulation.

In response to RQ1, patriotism was linked to higher emotion suppression scores. For emotion reappraisal, the overall model was significant, and there was also a sig-nificant interaction between training video exposure condition and nationalism (see Figure 1). For participants exposed to the tactical video, nationalism was positively related to emotion reappraisal (unstandardized simple slope = .23). For participants exposed to the emotional video, nationalism was negatively related to emotion reap-praisal (unstandardized simple slope = −.14).

Metacognition. Table 5 displays the results for participants’ metacognition cognitive self-consciousness and metacognition need to control thoughts scores after playing the videogame mission. Contrary to H2, individuals who viewed the emotional training video reported higher cognitive self-consciousness after playing the videogame mis-sion than those who viewed the tactical video. This resonates with a near-significant finding for the same variable prior to playing the videogame.

For need to control thoughts, the overall model was significant. However, only the control variable of need to control thoughts at the initial online survey significantly predicted need to control thoughts after playing the videogame training mission.



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Overall, after playing the training game mission, there was no support for H2, and the cognitive self-consciousness results were in the opposite direction. The implications of this finding appear in the “Discussion” section.

Number of rifle shots. Table 6 displays the results for a Poisson regression that exam-ined the effects of the training videos, along with patriotism and nationalism effects on number of rifle shots in the game mission. The overall model was not significant, and neither of the predictor variables was significantly related to the number of rifle shots fired.

In sum, after the videogame mission, emotional training video exposure increased metacognition cognitive self-consciousness scores. Additionally, there was an interac-tion effect combining prior training video exposure and nationalism on emotional reappraisal scores.

DiscussionWe assessed the cognitive readiness effects of exposure to military training videos, along with the effects of trainee nationalism and patriotism. This study focused on military cognitive readiness outcomes, such as emotion regulation and metacognition (Morrison & Fletcher, 2002). The study also examined transfer effects to clarify how training video exposure affected the way participants later played a military video-game, along with post-game emotion regulation and metacognition outcomes. Metacognition is an important factor because it is related to vigilance, conscious awareness, and involvement when learning from TV and audiovisual content (Salomon,

Table 5. Hierarchical Regressions Predicting Metacognition After Playing a Videogame Mission (N = 117).

Metacognition cognitive self-consciousness

Metacognition need to control thoughts


Step 1: Metacognition at baseline survey

.65 .08 .60*** .36*** .60 .09 .54*** .30**

Step 2: Video condition −.09 .04 −.15* .02 .02 .04 .05 .01Patriotism .002 .04 .01 −.02 .04 −.04 Nationalism .03 .05 .05 .02 .05 .04 Step 3: Interaction between



.04 .05 .07 .03 .05 .05

Note. Cognitive self-consciousness: total R2 = .38; adjusted R2 = .35. F(6, 116) = 11.37, p < .001. Need to control thoughts: total R2 = .30; adjusted R2 = .27. F(6, 116) = 8.16, p < .001.† p < .10. *p < .05. **p < .01. ***p < .001.




Table 6. Poisson Regression Predicting Rifle Shots (n = 92).

Rifle shot counts

Predictor variables B SE BWald’s chi-

square df Significance

Intercept .52 .12 18.98 1 .000Tactical video −.20 .18 1.23 1 .26Emotional video 0 Tactical × Patriotism centered .25 .11 1.51 1 .24Emotional × Patriotism centered −.20 .11 0.04 1 .85Tactical × Nationalism centered .01 .12 0.006 1 .94Emotional × Nationalism centered .07 .14 0.28 1 .60

1983). In addition, media exposure can affect people’s emotions and, in turn, these emotions influence subsequent perceptions and behaviors (Goldberg et al., 1999; Nabi, 2003a).

After single exposure, the military training videos had significant short-term effects on some but not all of participants’ cognitive readiness scores. Participants exposed to the emotional training video were less able to suppress their emotions compared with those exposed to the tactical training video. They also reported less of a need to control their own thoughts relative to participants exposed to the tactical training video. This highlights how media exposure can lead to affective reactions on viewers (Goldberg et al., 1999; Nabi, 2003a), and how negative emotions can decrease metacognition, in this case need to control thoughts (Clore & Huntsinger, 2007). These results are con-gruent with media priming research documenting how movies and music videos have priming effects on subsequent responses (Roskos-Ewoldsen et al., 2009).

The findings also exemplify how the tone of military training videos affects cogni-tive readiness outcomes in the short term. Future studies should determine whether these effects are short lived or extend over time. For example, although most research-ers assume that priming effects only operate in the short term, priming episodes can also operate for decades after exposure (Mitchell, 2006). Repeated exposure effects also deserve attention, as it is expected to cultivate attitudes congruent with media content (Gerbner et al., 2002). For example, playing prosocial videogames was associ-ated with increased perspective-taking and sympathizing (Vieira, 2012). In addition, perspective-taking and sympathizing positively correlated with thoughts about whether violence was “justified” or not (Vieira, 2012). However, playing violent videogames was negatively related to perspective-taking and sympathizing, and perspective-taking and sympathy were negatively associated with acceptance of unjustified violence (Vieira & Krcmar, 2011). Following this, future studies should examine whether play-ing aggressive or prosocial videogames is linked to acceptance of violent action in military training games.

The results have implications for military cognitive readiness research. Exposure to military training videos affected participants’ metacognition and emotion regulation



Peña and Brody 17

processes, and media priming mechanisms may help explain such short-term cognitive readiness outcomes. This provides a theoretical foundation that allows researchers and practitioners to draw specific predictions about the outcomes of technology-based military training. From a practical standpoint, it is worth noting that single-exposure military training videos had reliable effects on cognitive readiness factors and, thus, continued study of video training technologies such as Leader Challenge seems justi-fied by the results. Also, one contribution of this study is proposing and testing con-crete measures of cognitive readiness constructs. As noted above, previous research had not tested the reliability of the proposed measures, nor collected evidence for the suggested theoretical mechanisms (Fletcher & Wind, 2011; Grier, 2012). This implies that the selected scales discerned short-term metacognition and emotion regulation changes as a result of exposure to training technologies.

At first blush, readers may conclude that military training should not include emo-tional content, as cognitive readiness will be reduced. Instead, the results need to be placed in a broader context. The experiences depicted in the training technologies described here attempt to sensitize trainees to situations that could occur later. The rationale is that if comrades’ deaths and uncertain target identification may occur, it is best to be mentally ready for it (see Fletcher & Wind, 2011). Being mentally prepared for the unexpected is the very definition of military cognitive readiness (Morrison & Fletcher, 2002). This is akin to the assumptions of inoculation theory, in which previ-ous exposure to arguments or situations is expected to bestow resistance to the actual event (Pfau et al., 2001). This aim is also congruent with attempts to bestow stress resilience by using virtual environments before deployment to lessen future adverse effects (Rizzo et al., 2012). Future studies should examine whether training technolo-gies with different doses of negative emotion are equally effective at conferring inocu-lation (see Nabi, 2003b).

After exposure to the training videos, the participants played a military training first-person shooter videogame. We looked for evidence of transfer effects, a dimen-sion of cognitive readiness concerned with previous training manifesting itself in sub-sequent contexts (Morrison & Fletcher, 2002). Contrary to our prediction, after playing the military videogame, participants previously exposed to the emotional training video had comparatively higher metacognition cognitive self-consciousness scores (e.g., “I am constantly aware of my thinking”). As noted above, one explanation is that combined exposure to the emotional training video and the videogame sensitized par-ticipants to unpleasant experiences and, in turn, they were more conscious of their thoughts. This mechanism is also hinted at by the near-significant finding for metacog-nition cognitive self-consciousness after participants viewed the emotional training video and before playing the videogame. After playing the videogame, the negative association between emotional video exposure and cognitive self-consciousness became significant. Based on the manipulation check, the emotional video activated negative emotions, death, and concerns for family and friends. Moreover, the training videogame also featured difficult choices including opening and ceasing fire, interro-gating suspects, and risking lives (CAPE, 2013). It is likely that these tense emotional experiences led participants to be more aware of their thoughts. One possibility is that




awareness of one’s thoughts reflects metacognitive processes linked to vigilance and engagement as a result of media exposure (Salomon, 1983). Increased awareness of one’s thoughts after watching the emotional video and playing the game mission is also congruent with how exposure to negative and unpleasant videos increased atten-tion and augmented mental effort relative to non-negative videos (Lang, Newhagen, & Reeves, 1996).

No behavioral transfer effects were observed. Single exposure to training videos did not affect the number of in-game rifle shots fired by participants. This suggests that, compared with in-game behavior, metacognitive and emotional control compo-nents were more amenable to short-term changes after exposure to Army training tech-nologies. Alternatively, perhaps we needed to look at other behavioral outcomes that might have revealed transfer effects (e.g., decision reaction time). Future studies should continue investigating possible behavioral transfer effects.

Patriotic and nationalistic trainees were expected to react differently in technology-enabled military training as similar media experiences generate different outcomes by activating group prototypes and social norms on users (Hogg & Reid, 2006). This hypothesis had not yet been tested in relation to cognitive readiness outcomes. For participants exposed to the emotional video, nationalism was negatively correlated with emotion reappraisal after the videogame mission. However, for participants exposed to the tactical video, nationalism was positively correlated with emotion reap-praisal (see Figure 1). Why was emotional reappraisal increased among people with lower nationalism scores exposed to the emotional video? And why was emotional reappraisal increased among people with higher nationalism scores exposed to the tactical video? One possible explanation is that training technologies exposed partici-pants with low nationalism to extreme situations that perhaps they do not often think about or even might politically oppose. This assumes that nationalistic participants were more shocked by the content of the training technologies and attempted to change their emotions. This account capitalizes on research indicating that more nationalistic people showed more support of aggressive foreign and national security policies (Federico et al., 2005; Williams et al., 2008). Congruent with this reasoning, it is also possible that the tactical training video depicting the possibility of killing civilians could have challenged the expectations of more nationalistic trainees, which tend to hold more hawkish attitudes that justify aggressive foreign policies (Federico et al., 2005). It is possible that this triggered attempts to control contradictory thoughts. This reasoning is akin to cognitive dissonance effects (Festinger, 1957), in which people exposed to contradictory information strive to reduce mental dissonance caused by holding opposing thoughts. Future research should investigate possible cognitive dis-sonance effects resulting from training technologies that challenge trainees’ social identity.

Finally, patriotism was linked to increased emotion suppression scores, implying higher emotion control among more patriotic participants. Though this effect has not been documented before, one explanation is that more patriotic participants were more capable of putting emotion aside because patriotism normalizes the difficulties of mili-tary training (Cigrang et al., 2000). For example, patriotism is expected to influence



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stress management and encourage trainees to persevere (Cigrang et al., 2000). Future research needs to confirm whether patriotic trainees are more prone to try to keep emo-tions under control when exposed to military training technologies. Overall, these results lend some support to the hypothesis that social identification modulates media exposure effects (Mastro et al., 2008; Reid et al., 2007), and expand the research con-texts amenable to SIT and SCT (Hogg & Reid, 2006). In addition, this suggests that patriotism and nationalism should be added to the list of personal characteristics that influence cognitive readiness outcomes (see Grier, 2012).

LimitationsThe present research has several limitations. First, the external validity of this study is limited due to using a sample of college students without military experience. Future studies should look into the cognitive readiness effects of training technology expo-sure in more experienced samples. In addition to its theoretical focus and method, the present study could be still useful to future meta-analyses comparing effects across samples. Second, this study featured no control group. The lack of a control group does not allow us to conclude whether the emotional or tactical videos increased or decreased a particular outcome relative to the control group. However, the study con-trolled for metacognition and emotion regulation before exposure, therefore implying that training video exposure and nationalism effects reported above operated above and beyond participants’ baseline self-assessments. Also, the metacognition need to control thoughts scale had low reliability and, thus, its results should be cautiously interpreted. Another potential limitation relates to the relatively small effect sizes—particularly the ∆R2 for the second and third blocks of the regressions. However, 2% to 3% variance accounted for is a sizable number when considering both the lasting effects of primes (e.g., Mitchell, 2006), possible repeated exposure and cultivation effects (Gerbner et al., 2002), and the potentially wide distribution of training videos to thousands of trainees. We contend that the cumulative effects of the training videos on such a scale would be noticeable.

ConclusionThe impact of military training technologies lies at the intersection between academic and practical interests. In a sample with no combat experience, cognitive readiness outcomes were affected by exposure to military training videos, along with trainee nationalism and patriotism. The continued study of training media exposure and per-sonal factors can help us gain more accuracy when assessing the impact of military virtual training technologies.

AcknowledgmentsThe authors would like to thank Chris Miller and Nate Self at the Praevius Group for providing access to the military training technologies featured in this study. Many thanks to Mike Roloff and four anonymous reviewers for their helpful comments. We also thank Natasha Ahmed,




Tyler Durman, Raef Lambert, Xavier Salinas, and Emma Ourston for their help in collecting data, and Reed Daw, James Klepfer, Gabriel Pantoja, and Garrett Villarreal for their assistance in coding data.

Declaration of Conflicting InterestsThe authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

FundingThe authors received no financial support for the research, authorship, and/or publication of this article.

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Author BiographiesJorge Peña (PhD, 2007, Cornell University) is an assistant professor in the Department of Communication at University of California, Davis. His research focuses on cognitive, affective, and behavioral processes involved in online collaboration and play.

Nicholas Brody (PhD, 2013, The University of Texas at Austin) is an assistant professor in the Department of Communication Studies at the University of Puget Sound. His research interests include cyberbullying, language use in mediated communication, and communication in per-sonal relationships.


Increasing Cognitive Readiness Through Computer and Videogame–Based Training

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