The Impact of Resilience and Grit on Inductive and Deductive Reasoning Following

Exposure to Combat-Like Environments of US Military Recruits

In the past decades, a number of acts of terror have exposed individuals to combat-like environments; these situations have been shown to produce mental health conditions such as depression and post-traumatic stress disorder (PTSD). These conditions can impact reasoning. Reasoning is the ability to apply logic and validate information acquired, in order to make sense of it, and either justify or alter thoughts and practices based on that information (Diamond, 2013). Combat environments place significant pressure on even well-trained veteran military personnel which can extensively impair the ability to reason (Blanchette, Richards, Melnyk, & Lavda, 2007; Lieberman, Bathalon, Falco, Morgan, Niro, & Tharion, 2005b). For example, following exposure to combat, soldiers must reason whether an environment is safe.

Almost all duties performed in combat (before, during and after) involve cognitive functions, such as reasoning. Adverse environments like combat can extensively impair the ability to execute such cognitive tasks (Lieberman et al., 2005b). During combat, soldiers must be able to make decisions and reason efficiently and swiftly; any cognitive impairment can cause detrimental effects. This known devastating effect on cognitive processing, which was referred to as “fog of war” by Carl von Clausewitz, can describe a soldier’s mental state during combat (Lieberman et al., 2005b).  For example, Small, Lerner, and Fischhoff (2006) showed how participants’ anger and sadness differentially influenced causal judgments about the attacks of September 11th; results explored how participants’ anger caused more causal attributions than their feelings of sadness. In another example, David, Farrin, Hull, Unwin, Wessely, and Wykes (2002) assessed the deployed and non-deployed veterans’ attention and memory following exposure to the Persian Gulf War; their findings revealed that deployed veterans showed decreased attention and memory than non-deployed military veterans.

While there is anecdotal documentation (i.e., soldier narratives) that depicts the impact of combat-like environments on the ability to reason, there still is a need for scientific research to investigate reasoning following such exposure (Lieberman et al., 2005). The studies that have investigated this impact have indicated that following such exposure, cognitive processing and performance worsens (Blanchette & Richards, 2004; Lieberman, Bathalon, Falco, Kramer, Morgan, & Niro, 2005a; Lieberman et al., 2005b; van Liempt, van Zuiden, Westenberg, Super, & Vermetten, 2013). However, these studies have not investigated whether an individuals’ grit and resilience, two positive psychology constructs that play an integral role in human performance, can impact reasoning (Duckworth, Peterson, Matthews, & Kelly, 2007; Matthews, Eid, Kelly, Bailey, & Peterson, 2009; Southwick, Bonanno, Masten, Panter-Brick, & Yehuda, 2014). With grit, an individual is able to perform vigorously toward challenges without losing energy over an extended period of time regardless of failure (Duckworth et al, 2007). With resilience, an individual is able to appropriately adapt to significant trauma or adversity (Bonanno, 2004; Southwick et al., 2014). Adverse environments can play an important role in shaping individuals’ cognitive development; their presence leads to neurological and physiological concerns which influences the way cognition functions (Ogle, Rubin, & Siegler, 2013). Grit and resilience, two subtly different positive psychology constructs, are essential in the successful adjustment of an individual’s mental state after challenging experiences that induce trauma and stress (Mobbs & Bonanno, 2018). Therefore, it is reasonable to hypothesize that both constructs somehow affect the ability to reason. This study examines whether these constructs impact reasoning following exposure to adverse environments.

Impact of Adverse Environments on Deductive and Inductive Reasoning

Reasoning is essential to human interaction as it is the process of a logical way of thinking; it is significantly correlated to critical thinking, problem solving, intellect, and decision making (Walker, Leary, Hmelo-Silver, & Ertmer, 2015). Philosophers identify three all-encompassing categories of reasoning: deductive, inductive, and abductive reasoning (Diamond, 2013). In deductive reasoning, inferences are constructed logically through valid conclusions from a set of premises. In inductive reasoning, inferences are constructed logically through broad generalizations from a set of premises. In abductive reasoning, inferences are constructed by an insufficient set of observations to reach the most probable explanation. This study refrained from investigating abductive reasoning. While soldiers do utilize abductive reasoning, soldiers are often asked to utilize facts or generalizations before they abduce a guess from observation.

Adverse environments have shown to influence deductive reasoning. Specifically, such adverse contexts worsen normative thinking and lead to reduced accuracy in judgment (Blanchette, 2006; van Liempt et al., 2013). As with the research on deductive reasoning, research on inductive reasoning has also shown that such adverse circumstances are influential. Particularly, this includes decreased accuracy of judgment, deteriorated cognitive processing, and diminished decision making (van Liempt et al., 2013). Furthermore, mood and affect are highly influential in reasoning as they shape judgment, logic, and interpretation (Blanchette et al., 2007; Blanchette & Richards, 2010). It would make sense then, that experiences and environments that induce such affect also influences reasoning.

In 2005a, Lieberman et al. investigated the impact of simulated combat and non-combat on cognitive functioning among Navy Seals and Army Rangers; participants performed poorly on a number of cognitive functions (e.g., memory, reasoning) after exposure to simulated combat. In another study using only Army officers, Lieberman et al. (2005a) showed considerable decreases in cognitive functions following exposure to simulated combat, suggesting that such adverse conditions produce negative effects on reasoning. This investigation served as another example of the detrimental effects of adverse environments on cognitive performance.

In 2004, Blanchette and Richards found that combat experienced veterans who were exposed to combat-related syllogisms were more likely to make errors in reasoning than those who were not exposed to combat-related syllogisms. Blanchette and Caparos (2016) further compared the reasoning abilities of thirty-two veterans, half of whom were diagnosed with PTSD and half of whom did not have a PTSD diagnosis. Overall, veterans diagnosed with PTSD were more likely to reason inaccurately and illogically and perform worse overall in the reasoning tasks than the other veterans. In another study by Blanchette and Campbell (2012), researchers showed that British veterans with combat exposure performed worse on reasoning tasks with combat-related content compared to British veterans with no combat exposure who performed better on reasoning tasks with combat-related content.

As previous work has shown, adverse environments like combat have been linked to cognitive decline. The current study investigates individuals’ reasoning and expands that research by exploring how individuals’ resilience and grit impacts these outcomes. It is important to note that in this study, unlike previously aforementioned studies, individuals with previous combat/military experience were excluded from the study due to potential for re-traumatization as both Bravemind and Virtual Battlespace 3 (VBS 3) simulated Iraqi environments and included improvised explosive devices (IEDs) and missile and gun fire sounds.

Resilience and Grit as Factors in Reasoning

Resilience has been researched in various environments and contexts, which adds to the complexity of its operationalization (Southwick et al., 2014). While the definition of resilience continues to be measured and analyzed, there are numerous factors agreed upon. Resilient individuals are not without negative thoughts and emotions. Instead, they are more likely to possess coping skills and mechanisms to efficiently and effectively navigate through trauma, and successfully balance positive with negative feelings. Resilient individuals have the tendency to bounce back from a negative experience with competent functioning (Southwick et al, 2014).

Grit has been identified as a trait that allows an individual to perform vigorously and persistently toward challenges without losing energy or effort over a long period of time regardless of disappointment or failure (Duckworth et al., 2007). Grit promotes a perseverance of effort in prevailing over challenges that individuals must face on the path to success and is utilized as a catalyst for achievement realization (Matthews et al., 2009). Gritty individuals are more likely to self-regulate their feelings of commitment over a long time, regardless of any challenges or failures they might face. Research has shown that individuals who are gritty are more likely to be successful and accomplished; gritty individuals are more likely to characteristically possess traits that are above a normal person’s ability (Duckworth et al., 2007).

The positive psychology constructs of resilience and grit play an integral role in personality and performance (Duckworth et al., 2007; Southwick et al, 2014). Grit and resilience are essential in the successful adjustment of an individual’s mental and cognitive state following challenging contexts like combat (Duckworth et al., 2007; Southwick et al, 2014). Furthermore, both grit and resilience have been positively associated with a number of cognitive functions. For example, grit has been shown to be positively linked to successful problem-solving in college students (Arslan, Akin, & Çitemel, 2013; Kalia, Fuesting, & Cody, 2019; Keegan, 2017), flexibility in cognition (Arslan et al., 2013; Kalia et al., 2019), effective thinking and metacognition (Arslan et al., 2013), and language learning and acquiring (Keegan, 2017). Resilience is positively correlated to perception and self-perception (Cazan & Dumitrescu, 2016), cognitive ability in trauma survivors (Cazan & Dumitrescu, 2016), and problem-solving in undergraduates (Li, Eschenauer, & Persaud, 2018).

While these two positive psychology constructs have overlapping qualities, there are numerous differences. The existence of grit does not demand an adverse environment or situation as it is not dependent upon sustaining effort through a critical incident, however, this is not the case with resilience (Georgoulas-Sherry & Kelly, 2019). Resilience is categorized as an active process of positive adaptation where an effort is made to continue and maintain homeostasis during traumatic or challenging circumstances (Mobbs & Bonanno, 2018). Additionally, grit is different from resilience due to the degree of perseverance and passion placed on achieving a goal regardless of hardship; in resilience, there is no goal attainment. Georgoulas-Sherry & Kelly (2019) revealed that resilience and grit are empirically different from each other and should not be used synonymously.

While previous research has established the importance of the positive psychology constructs of resilience and grit, no studies have examined individual cognitive differences following exposure to adverse environments. Based on their role in supporting successful adjustment, resilience and grit might mitigate negative impacts on reasoning in individuals exposed to combat situations.

Immersive versus Non-Immersive Technology

The U.S. Army has implemented numerous immersive and non-immersive technologies to train soldiers on how to perform in the field (Kim, Rosenthal, Zielinski, & Brady, 2014). Immersive technologies allow an individual to be fully immersed in a simulated environment through tactile, auditory, and visual apparatuses such as head mounted tracking systems, vibrating floorboards, and body sensors. Non-immersive technologies allow an individual to participate in an environment in a less immersive fashion, through a screen and controller; non-immersive technologies provide limited display (e.g., auditory, visual) capacity. While both technologies allow a user to engage with a computer simulated environment, interaction and presence are hallmark characteristics in distinguishing these technologies apart. Non-immersive technologies provide the least interactive application such that interaction typically occurs through two-dimensional apparatuses (e.g., computer, keyboard) with the user feelings the least present within that technology. Immersive technologies, however, provide the most interactive application such that interaction typically occurs through three-dimensional apparatuses (e.g., vibrating floorboards, head mounted tracking systems) with the user feelings the most present within that technology.  Furthermore, Suh and Prophet (2018) have examined how the features from both immersive and non-immersive technologies trigger a user’s cognition and elicit cognitive responses. For example, through immersive technologies, immersion allows for the capability to cognitively acquire, retain, and process information, augmenting human cognition. Regardless of immersive or non-immersive technologies, game content also elicits a cognitive response (e.g., immersive or non-immersive technologies with horror content triggers fear and anxiety). Additionally, research has shown that immersive and non-immersive technologies can produce flow (i.e., psychological state in which one feels focused, involved, and absorbed in the activity or context).and situated cognition (i.e., when learning is enhanced in a situated activity or context); as the technology becomes more immersive, flow and situated cognition is elicited. Research has shown that immersive and non-immersive technologies can induce real-world affect and arousal (Ivory & Kalyanaraman, 2009; Kim et al., 2014). Ivory and Kalyanaraman (2009) assessed that participants engaged in the immersive simulation reported more violent than participants in the non-immersive simulation. Tamborini, Eastin, Skalski, and Lachlan (2004) revealed that participants in an immersive condition exhibited more aggressive feelings than participants in non-immersive condition. Recent work has evaluated immersive and non-immersive technologies as a potential medium in the treatment of numerous mental health and cognitive disorders and impairments through trauma exposure; specifically, clinical research has shown great promise in using such technologies in efforts to treat mental and cognitive problems such as phobias and PTSD (Maples-Keller, Bunnell, Kim, & Rothbaum, 2017). Due to potential for re-traumatization, expensive technology costs, in-depth training, and small sized effects, immersive and non-immersive technologies can be disadvantageous as well (Fodor, Coteț, Cuijpers, Szamoskozi, David, & Cristea, 2018; Maples-Keller et al., 2017); for example, potential for re-traumatization and virtual reality sickness (i.e., symptomology similar to motion sickness such as nausea and disorientation) impacted inclusion and exclusion criteria in this study. This study added to previous research by exploring the impact of immersiveness on reasoning by evaluating whether participants in the immersive conditions performed better or worse on the deductive and inductive reasoning tasks than participants in the non-immersive conditions. In terms of apparatuses, to the authors’ knowledge, VBS 3 has never served as a research stimulus, but Bravemind has been utilized in prior studies (Rizzo et al., 2012, 2013).

Current Study

While the aforementioned work has established the negative impact of combat on reasoning in service members, there are limitations in this work. This study aims to assess how individuals inductively and deductively reason following exposure to computer-simulated combat-like environments, and further analyzes the impact of resilience and grit on reasoning following exposure to such combat environments. Hypotheses include:

Hypothesis 1a: Individuals in the simulated combat conditions would performance worse on the deductive and inductive reasoning tasks than individuals in the non-combat conditions.

Hypothesis 1b: Individuals in the immersive conditions would performance worse on the deductive and inductive reasoning tasks than participants in the non-immersive conditions.

Hypothesis 2a: Highly gritty or resilient individuals would perform better, overall, on the reasoning tasks than less resilient or gritty individuals.

Hypothesis 2b: Individuals who reported higher grit or resilience would perform better, overall, on the reasoning tasks following exposure to simulated combat than individuals who reported lower grit or resilience.

Methods

 Participants

107 participants (66% men and 34% females) were drawn from a private military institution.  Most participants (ages 18 to 22) were 18 (34%) or 19 (38%). Most participants were freshmen (40%) or sophomores (34%). Participants majored in Psychology (36%), Computer Security (19%), or other disciplines (45%). Individuals with previous combat/military experience were excluded from the study due to potential for re-traumatization as the stimuli on both Bravemind and VBS 3 simulated Iraqi environments included improvised explosive devices (IEDs) and missile and gun fire sounds. Additionally, individual who were 17 years or younger, and/or had sensitivity to virtual reality (e.g., nausea, disorientation, headache) were excluded from the study. Individuals who self-reported being mentally healthy and were in the U.S. Corp of Cadets were included in this study.

Materials and Apparatuses

Deductive Reasoning Task                                

Overton’s (1990) Wason Selection Task is composed of a series of 20 conditional propositions in which a participant is asked to choose the condition(s) that validate the rule. An example item includes: “Suppose each card has an action on one side and a result on the other. Which of these card(s) are worth turning over if you want to know whether the statement below is false? If a person is drinking beer, then the person must be over 21.” In this study, Overton’s (1990) Wason Selection Task was split into a pretest and posttest deductive reasoning task.

Inductive Reasoning Task

The Letter Sets Test consisted of a 30-item test, which came from the French Kit of Reference Tests for Cognitive Factors (Ekstrom et al., 1976); each item consisted of five sets of letters with four letters per set. These four letters per set followed a certain pattern and participants were asked to find this pattern to differentiate between the similar four like sets and the different one. It has been validated in multiple populations, including college-aged students (Larsson & Von Stumm, 2015). An example item includes: “Which four letter set is different from the others? QPPQ HGHH TTTU DDDE MLMM.” In this study, the Letter Sets Test was split into a pretest and posttest inductive reasoning task.

The pretest and posttest deductive and inductive reasoning task mirrored one another; the questions were split across tests in an arbitrary order to avoid familiarity. The order of tasks was counterbalanced, and the problem order was not randomized. By splitting items, there was a presumption that the questions would test the same content. Intra-class correlation analysis (ICC) were conducted to verify that the pretest and posttest were highly correlated; per guidance from Shrout and Fleiss (1979), a 2-way mixed-effects ICC model was employed.

Grit Scale (Duckworth et al., 2007)

The first (self-report) scale, the 12-item Grit Scale, assesses “trait-level perseverance and passion for perseverance for long-term goals” (Duckworth & Quinn, 2009, p. 166). Items included “Setbacks don’t discourage me” and “I have achieved a goal that took years of work.” The Grit Scale shows high internal consistency (a = .85) overall, including Perseverance of Effort (a = .78) and Consistency of Interests (a = .84) (Duckworth et al., 2007).

Resilience Scale for Adults (RSA) (Wagnild & Young, 1993)

The second (self-report) scale, the RSA, is a 32-item scale that consists of intrapersonal and interpersonal protective factors presumed to facilitate adaptation to psychosocial adversities (personal strength, social competence, structured style, family cohesion, social resources). Questions included “My life has meaning” and “I am determined.” Cronbach’s alpha coefficients

ranged from .72 to .94 supporting the internal consistency reliability of the RSA.

Bravemind

Bravemind is an immersive, virtual reality system that simulates Iraqi environments; stimuli include IEDs and missile and gun fire sounds. Users wear a head mounted display system which orients them within the simulation and utilize a video game controller to move around the simulation A vibro-tactile floorboard, Rumblefloor, is utilized to simulate the combat environment vibrations.

Virtual Battlespace 3 (VBS3)

VBS3 is a first-person military training non-immersive simulation. VBS3 simulates combat scenarios and is utilized for tactical training and mission rehearsal. Participants use a standard laptop, a keyboard, a mouse, and headphones.

Design                                                                                        

Participants were placed in one of four conditions: Bravemind with simulated combat (n = 27) or non-combat (n = 27) or VBS3 with simulated combat (n = 26) or non-combat (n = 27). Overall, individuals in the simulated combat conditions drove on an Iraqi desert road while being exposed to IEDs and missile and gun fire. Individuals in the simulated non-combat scenario, completed the same scenario (i.e., driving on an Iraqi desert road), but were not exposed to the combat stimuli (i.e., there were no IEDs or missile and gun fire and instead no sound).

Individuals who took part in the Bravemind simulated combat scenario condition, wore a head mounted display system which oriented them within the vehicle while utilizing a video game controller to drive on an Iraqi desert road; the participants also sat on top the Rumblefloor, and during the exposure to IEDs and missile and gun fire, the Rumblefloor simulated the combat environment vibrations. Individuals who took part in the Bravemind simulated non-combat scenario condition, wore a head mounted display system which oriented them within the vehicle while utilizing a video game controller to drive on an Iraqi desert road; while the participants sat on top the Rumblefloor, there was no exposure to IEDs and missile and gun fire, and therefore, the Rumblefloor made no vibrations. Individuals who took part in the VBS3 simulated combat scenario used a standard laptop, a keyboard, and a mouse to drive on an Iraqi desert road, and with the use of headphones were able to be exposed and hear IEDs and missile and gun fire. Individuals who took part in the VBS3 simulated non-combat scenario used a standard laptop, a keyboard, and a mouse to drive on an Iraqi desert road; while participants donned headphones, there was no exposure to IEDs and missile and gun fire, and participants heard no sound.

While participants utilized one of the two apparatuses, a VBS3’s scenarios (both combat and non-combat) was created to mirror the Bravemind’s scenarios. Therefore, participants completed comparable scenarios which allowed for comparison of the apparatuses.

Procedure

The study was approved by Teacher’s College, Columbia University’s Institutional Review Board. Volunteers were recruited by word of mouth and received credit for participation.Data collection was conducted over two weeks. First, participants were asked to complete the pretest deductive and inductive reasoning task for 15 minutes using Qualitrics. Second, participants partook in one of the conditions for ten minutes; the ten-minute timespan for the computer simulation was provided in efforts to avoid any potential desensitization to the stimuli. The block randomization method was used to confirm equal sample size for conditions and the reasoning task order. Prior to participation of computer simulation, researchers provided a quick tutorial in using apparatuses. Third, immediately following participation in one of the conditions, participants were then asked to complete the posttest deductive and inductive reasoning task for 15 minutes using Qualitrics. A week after completing the first part of the study, participants received a Qualitrics link to complete the scales. Participants were also asked about their age, gender, mental health, and major including their past experience with the apparatuses.

Results

Two 2x2x2 mixed design ANCOVAs were utilized to investigate individuals’ ability to reason following simulated combat-like environments. The first 2x2x2 ANCOVA included pretest and posttest deductive reasoning task scores as the within-subjects factors, simulation (two levels: combat or non-combat environment) and immersiveness (two levels: immersive and non-immersive virtual reality) as the between subjects factors, and grit and resilience as the covariates. The second 2x2x2 ANCOVA differed only in within-subjects factors as this included pretest and posttest inductive reasoning task scores. An alpha level of .10 was utilized for each hypothesis under Theise, Ronna, and Ott (2016)’s guidance who suggest that the convention of p < .05 “can be negatively impacted by small sample size, bias, and random error, and has evolved to … acceptance of statistical significance for p > .05 for complex relations such as effect modification” (E928). Due to the exploratory nature of this research endeavor and the impact of the covariates (i.e., the third factor of grit and resilience in evaluating the impact on inductive and deductive reasoning following exposure to combat-like environments of US Military recruits), the authors of this project employed the modified a level as recommended by Theise et al. (2016). Using G*Power 3.1.9.2 to conduct power analysis, a sample size of 108 participants was targeted for medium-sized effects (Cohen’s f = .32) with acceptable statistical power (0.80) (Faul, Erdfelder, Buchner, & Lang, 2009). Most participants reported no experience with VBS3 (96%) and Bravemind (97%); the individuals that reported experience never utilized the apparatuses and were included in the study.

Performance Metrics and Scoring Procedure

Intra-class correlation analysis (ICCs) were conducted to verify that the pretest and posttest were highly correlated. A high degree of reliability was found between the deductive reasoning measurements; the average measure ICC was .64 with a 95% confidence interval (CI) from .47 to .76 (F(106, 106) = 2.92, p < .001) (SEM = 2.74, MDC = 7.63). For inductive reasoning tasks, though, the average measure ICC was .05 with a 95% CI from -.31 to .32 (F(106, 106) = 1.06, p = .39, NS) (SEM = 2.56, MDC = 7.11) suggesting that the inductive reasoning tasks were not correlated.

Overton’s (1990) scoring methodology was used for the Wason Selection Task. Ekstrom et al.’s (1976) scoring methodology was used for Letters Set Tests. However, the tests were split and there were separate composite scores for the first problems (e.g., pretest deductive or inductive task) and the second problems (e.g., posttest deductive or inductive task).

Priori Analysis

Pearson product-moment correlation coefficients assessed the relationship between the two constructs (r = .18, p = .05), suggesting that resilience was significantly correlated to grit (see Table 1). T-tests were utilized to determine baseline differences. The findings revealed no significant differences between participants in combat and non-combat conditions in terms of their deductive (t(105) = -1.13, p = .26, NS) or inductive reasoning (t(105) = -1.25, p = .22, NS) or between the immersive and non-immersive conditions in terms of deductive (t(105) = 1.01, p = .32, NS) or inductive reasoning (t(105) = -.90, p = .37, NS)

Table 1: Correlational Matrix of Study Measures

Hypothesis 1a: Simulation on Reasoning

Findings revealed a significant interaction between deductive reasoning and simulation condition, (F(1, 101) = 3.28, p = .07, η_p² = 0.03); participants assigned to simulated combat conditions showed an increase in deductive reasoning performance (M = 20.87, SD = 4.28) compared to participants assigned to simulated non-combat conditions (M = 18.02, SD = 4.43) (see Table 1). A significant interaction was found between inductive reasoning and simulation condition, (F(1, 101) = 26.16, p < .001, η_p² = 0.21); participants assigned to simulated combat conditions showed a reduction in inductive reasoning performance (M = 5.91, SD = 2.25) than participants assigned to simulated non-combat conditions (M = 8.58, SD = 2.38) (see Table 2).

Table 2: Tests of Between and Within-Subjects Effects: Deductive Reasoning

Hypothesis 1b: Immersiveness on Reasoning

Findings revealed a significant interaction between deductive reasoning and immersion, (F(1, 101) = 4.11, p = .05, η_p² = 0.04); participants assigned to immersive conditions showed an increase in deductive reasoning performance (M = 19.89, SD = 4.47) than participants assigned to non-immersive conditions (M = 19.01, SD = 4.66) (see Table 1). No significant interaction was found between inductive reasoning and immersion, (F(1, 101) = .72, p = .40, η_p² = 0.01, NS) (see Table 2). There was no main effect of immersiveness, (F(1, 101) = .31, p = .58, η_p² = 0.01, NS).

Hypothesis 2a: Grit and Resilience on Reasoning

Findings showed no significant interaction between deductive reasoning and resilience (F(1, 101) = .04, p = .84, η_p² < .01, NS), or deductive reasoning and grit (F(1, 101) = .02, p = .88, η_p² < .01, NS) (see Table 1). No significant main effects of resilience (F(1, 101) = 1.48, p = .23, η_p² = 0.01, NS) or grit (F(1, 101) = 1.08, p = .30, η_p² = 0.01, NS) were revealed. There was similarly no statistically significant relationship between inductive reasoning and resilience (F(1, 101) = 1.81, p = .18, η_p² = .01, NS). There was a significant interaction between inductive reasoning and grit (F(1, 101) = 3.33, p = .07, η_p² = .03) (see Table 2). No main effects of resilience (F(1, 101) = 1.20, p = .16, η_p² = 0.02, NS) or grit (F(1, 101) = .02, p = .89, η_p² < 0.01, NS) were revealed.

Table 3: Tests of Between and Within-Subjects Effects: Inductive Reasoning

Hypothesis 2b: Resilience and Grit x Immersiveness x Simulation on Reasoning

Findings revealed no statistically significant three-way interaction among grit, immersiveness, and simulation (F(1, 101) = .21, p = 0.93, η_p² = .01, NS) or resilience, immersiveness and simulation (F(1, 101) = .33, p = .86, η_p² = 0.01, NS). Similar results were revealed among grit, immersiveness and simulation (F(1, 101) = .79, p = .54, η_p² = .03, NS) and resilience, immersiveness and simulation (F (1, 101) = 1.41, p = .24, η_p² = .05, NS).

Discussion

With regard to the study hypotheses, our findings run mostly counter to our anticipation. In reference to hypothesis 1a, findings reveal that following simulation (i.e., combat versus non-combat), deductive reasoning improved while inductive reasoning decreased following exposure to the simulated combat conditions. While it was hypothesized that participants in the simulated combat conditions would performance worse on the deductive and inductive reasoning tasks than individuals in the non-combat conditions, this was not the case. This study revealed a significant increase in the accuracy of post-simulation deductive reasoning, a finding that is not in alignment with previous research and soldier narratives. The increase of performance in deductive reasoning following exposure to simulated combat curiously suggests that combat environments might positively impact some types of reasoning. 

In terms of hypothesis 1b, results suggest that following immersion (i.e., non-immersive versus immersive), post-simulation deductive reasoning improved. While it was hypothesized that post-simulation reasoning would decrease, this finding did align with previous research suggesting benefits from immersive technology (Kim et al., 2014). One possible reason for this finding could be that the immersive conditions may have moved participants from observation to immersion. Further, the findings suggest that following exposure to simulated combat environments, regardless of platform, performance on post-simulation inductive reasoning reduced, but performance on post-simulation deductive reasoning increased. This finding is in alignment with previous research and soldier narratives which suggest that inductive reasoning is less effective after combat experiences (Lieberman et al., 2005b). One possible reason for this finding could be that the exposure to combat-like environments produced cognitive overload, and consequently, impaired working memory; additionally, another possible explanation for cognitive overload could have included the lack of familiarity with the apparatuses. As inductive reasoning is dependent on working memory, potential issues such as cognitive overload might have yielded this decline (van Liempt et al., 2013). In reference to hypothesis 2a, a significant relationship was revealed between inductive reasoning and grit; specifically, participants who were grittier exhibited higher accuracy on post-simulation inductive reasoning than non-gritty participants. Hypothesis 2a was partially supported as highly gritty individuals, not highly resilient, would perform better, overall, on the inductive reasoning tasks, not the deductive reasoning tasks. According to Duckworth et al. (2017), highly gritty individuals are more likely to resist changing direction and strategies, which might have been useful in completing inductive reasoning tasks, where participants are asked to to construct inferences through broad generalizations from a set of premises, as compared to completing deductive reasoning tasks, where participants are asked to construct inferences through valid conclusions from a set of premises.

In terms of hypothesis 2b, this hypothesis was not supported as individuals who reported higher grit or resilience did not perform better, overall, on the reasoning tasks following exposure to simulated combat than individuals who reported lower grit or resilience. While grit and resilience were not statistically significant, a potential reason for this could be in part due to the short length of the study. For example, as explained by Duckworth et al. (2017), grit is “based on an individual’s passion for a particular long-term goal or end state” (1087). Therefore, this particular study might not have been able to create the passion that is needed to provoke gritty people into exceling in cognitive tasks. Possibly, the study did not promote enough interest for the participants to truly work on the different tasks to promote a perseverance of effort, and consequently, no significance was detected. While Duckworth and Quinn (2009) were able to attain significant findings on grit with a similar population, their stimuli included the execution of West Point’s rigorous summer training program, whereas this study involved a ninety-minute study with no overarching goal.

Limitations

A number of limitations should be taken into account when considering this study. The inductive and deductive reasoning tasks may not have been ideal; while they were validated assessments, these tasks were not genuine soldier experiences, which raises concerns of real-life applicability. Also, as shown via the ICCs (i.e., which were utilized to verify whether the pretests and posttests were highly correlated), this study suffered from lack of evidence on the equivalency of the pretest and posttest for the inductive reasoning tasks, creating some risks to reliability. Furthermore, while this study investigated the impact of the positive psychology constructs of resilience and grit on reasoning following simulated combat, it did not investigate the ideal length of recovery time needed from such exposure.

The scales utilized were self-report; while self-reports are a common methodology, there are many risks to consider. Also, this study did not obtain baseline resilience or grit or preliminary testing on these constructs. Additionally, the scales were completed a week following the initial study to avoid potential performance bias (e.g., participants reporting themselves as more gritty or resilient following simulated combat); however, it is important to note that the one-week lapse could have allowed for multiple confounding factors to influence self-perceptions, adding noise to the data. The length of the study was a potential limitation as this study might not have created the passion thought to be needed to provoke gritty people. This can also be said about resilience, which is typically dependent on adversity (Southwick et al., 2014). The one-week lapse also limited the conclusions of our findings in that this study could not evaluate reasoning directly following exposure, and instead, a week following exposure to an adverse environment.

Individuals with previous combat/military experience were excluded from the study; while this exclusion was due to potential for re-traumatization, participants with previous combat/military experience could have reacted differently to the conditions, and subsequently, their reasoning might have been impacted. Additionally, most participants reported no experience with VBS3 and Bravemind, however, all participants reported prior use of a variety of immersive and non-immersive technology.  While participants were provided with brief instructions to utilizing the apparatuses, the lack of exposure could potentially be a confounding factor in terms of reasoning abilities if participants were distracted by lack of familiarity of the apparatuses.

As this area continues to evolve, more research that looks at the impact of these constructs need to be conducted to provide stronger links among grit, resilience, and cognitive functions in both operational, non-operational, and longitudinal contexts. More measures would also be beneficial. For example, this study could have benefitted from diagnostic imaging and updated neuropsychological assessment in efforts to strengthen the measurement of the specific cognitive processes assessed and subsequently, the appropriate assessments for these processes. Importantly, this work does not account for how trauma impacts mental illnesses which influence cognition. Additionally, this study only evaluated reasoning, and did not consider potential interaction with other cognitive functions. Lastly, as this study evaluated the ability to reason, measuring affect, as it is influential in reasoning, would help in assessing whether short duration of exposure to the simulated combat-like environments would induce an emotional response such as one might expect in a real-life combat experience.

Implications

Soldier narratives have depicted the effects of combat environments on reasoning (Lieberman et al., 2005a). This study serves as one of the first scientific studies to investigate how the positive psychology constructs of grit and resilience can impact an individual’s reasoning following simulated combat. There is value in comprehending the impact of grit and resilience, and potentially, other positive psychology constructs on reasoning. As other positive psychology constructs, grit and resilience are integral to promoting successful cognitive adjustment (Duckworth et al., 2007; Southwick et al., 2014). Furthermore, as positive psychology promotes the importance and power of healthy physical and mental health and wellbeing, better understanding the impact of such constructs is essential in producing protective mechanisms that help individuals (Southwick et al., 2014).

As virtual reality environments become more central to military training, comprehending the effects of such technologies is essential in understanding performance in real-world environments (Blanchette & Campbell, 2012; Southwick et al., 2014). More studies that address the utility and validity of simulations can contribute to improving military success. This type of research may have potential to find more effective platforms through which to better protect and train people likely to be exposed to combat environments. The findings of this study provide evidence on how reasoning may manifest following exposure to combat environments, and what factors may influence that manifestation.

On behalf of all authors, the corresponding author states that there is no conflict of interest

On behalf of all authors, the corresponding author states that we acknowledge that the manuscript is not published elsewhere and that it is not submitted simultaneously for publication in another outlet.

On behalf of all authors, the corresponding author states that there is no conflict of interest including financial benefit or benefit that has arisen from the direct applications of this research.