MENTAL READINESS IN EMERGENCY RESPONSE TASKS

Activation

VaezMousavi et al. (2009) describe arousal as an energetic state above the basic arousal level of the human body's resting state. The rise of the arousal level is called activation, so that a higher arousal level is the result of activation (VaezMousavi et al., 2009). Aside from attentional focus, self-efficacy, and imagery, activation is a part of psyching-up, a mental preparation strategy for an upcoming task (Tynes & McFatter, 1987). Comparing different psyching-up strategies, activation was found to be most effective (Tynes & McFatter, 1987). In professional sports, the use of activation strategies led to better performance (Caudill et al., 1983; Parker et al., 2011). Because the relationship between performance and activation manifests itself in an inverted U-shape, performance peaks at medium levels of arousal so that it is important to prevent both overactivation and underactivation (Hebb, 1955). Hence, systematic activation can be used to increase MR, and thus contribute to successfully completing the task (Orlick, 2016).

Transferred to ERTs, activation plays an important role because essential decisions are to be made under time pressure. Because emergencies occur unexpectedly day and night, systematic activation can buffer against underperformance (Monk & Carrier, 1997). Consequently, the following hypotheses can be derived:

• H1a: Activation affects the perceived stress in ERTs

• H1b: Activation affects the task performance in ERTs

• H1c: Activation affects the operational success in ERTs

Attentional Control

Attentional control is about directing one's focus of attention to one or more stimuli (primary task) while simultaneously controlling distractions, which means inhibiting attention to other distracting stimuli (Heitz, 2005). Especially under pressure, in situations where primary tasks require critical decisions, it is important to focus attention and control distractions (Lohse et al., 2010). Orlick (2016) describes the abilities to fully focus and not be distracted by disturbances as two abilities that have an extremely large influence on performance. At the same time, they are reported to have the greatest potential for improvement of top athletes (Orlick, 2016; Orlick & Partington, 1988). The positive contribution of attentional control to MR manifests itself in very stressful situations when performance can become entirely dependent on the ability to focus (Orlick, 2016). For instance, attentional control was the best predictor for objective performance under stress in the study by Marquardt et al. (2018).

Because stress is related to misperception and attention deficits, which lead to limited information intake (Mahoney et al., 1998), attentional control is important in ERTs where seconds might be crucial and any additional information can make a difference to patients' lives. Hence, the following hypotheses can be drawn:

• H2a: Attentional control affects the perceived stress in ERTs

• H2b: Attentional control affects the task performance in ERTs

• H2c: Attentional control affects the operational success in ERTs

Goal Setting

In the goal setting theory, Latham and Locke (1979) describe the determining influence of goals on performance and goal attainment. Accordingly, challenging and specific goals lead to higher performance than simple and unspecific goals (Latham & Locke, 1979). In terms of goal setting, agreed-upon goals have been shown to be more beneficial in terms of attitudes and performance than predetermined goals (Latham et al., 1978; Ludwig & Geller, 1997; Sagie, 1996). In accordance with highly self-effective people's motivation increasing after failing to achieve a challenging goal, top athletes deliberately set challenging, realistic goals for each training unit to improve their performance (Ievleva & Orlick, 1991). Furthermore, athletes were shown to recover faster when setting respective goals because goal setting strengthens their persistence through adversity (Orlick, 2016). Hence, Orlick (2016) recommends setting short-term goals regarding MR because achieving them leads to higher self-confidence and long-term goals, such as stress reduction or reaching a certain level of performance, can be accomplished.

Due to their structure, ERTs do not involve the potential for goal setting until processing the actual ERT. Instead, goal setting can be looked at on an individual level. Preventing the same mistake being made again can thus be considered as a short-term goal which contributes to the long-term goal of striving for performance excellence. Therefore, the following hypotheses can be derived:

• H3a: Goal setting affects the perceived stress in ERTs

• H3b: Goal setting affects the task performance in ERTs

• H3c: Goal setting affects the operational success in ERTs

Imagery

Along with attentional control, imagery has proved to be the most important skill in terms of performance excellence in the field of sports (Orlick & Partington, 1988). Imagery is referred to as using all senses to visualize and simulate a course of action in one's mind as vividly as possible (Weinberg, 2008). There is a difference between the internal perspective, which describes the imagination from the ego-perspective, and the external perspective, which describes the imaginary simulation of the action from another person's external perspective on oneself (White & Hardy, 1995). Athletes use the internal perspective most commonly for activation shortly before performing a task (Orlick & Partington, 1986). In research, imagery has been proven to enhance both performance and success (Guillot & Collet, 2008; Reiser et al., 2011), but whether or not a person uses imagery largely depends on their belief in their own ability to use it successfully (Short, 2005). Because similar activation patterns are activated during imagery and during execution (Batula et al., 2017), imagery is associated with higher MR because the probability of successful performance in reality is increased (Orlick, 2016).

Considering the transfer to ERTs, imagery is an essential means to reduce reaction times in decision-making. This assumption is corroborated by physicians using imagery, too, and considering it to be the most useful method for improving performance (Ibrahim et al., 2015; Wetzel et al., 2011). Hence, the following hypotheses can be drawn:

• H4a: Imagery affects the perceived stress in ERTs

• H4b: Imagery affects the task performance in ERTs

• H4c: Imagery affects the operational success in ERTs

Relaxation

Relaxation is the reversal of activation. Because permanent high-level arousal affects health and performance negatively (Selye, 1955; Weinberg, 2010), it is important to control arousal (Hebb, 1955). Physical or mental relaxation techniques can be applied to counteract too much arousal (Hebb, 1955; Weinberg, 2010). Breath control, for instance, is a relaxation technique athletes use to lower their arousal level immediately before or at short breaks during the performance (Weinberg, 2010). Inducing physical relaxation, progressive relaxation (Jacobson, 1924) can be used which requires extensive practice to be applied to performance situations (Öst, 1987; Weinberg, 2010). Stress management training (Smith, 1980, cited in Weinberg, 2010) is a cognitive-affective relaxation technique which includes the evaluation of potential stressors and stress reactions prior to performance in order to practice appropriate reactions. Techniques used in stress management training are various relaxation techniques or self-talk (Smith, 1980, cited in Weinberg, 2010). Both stress management training and relaxation techniques have been proven to be effective in the fields of sports (Crocker et al., 2016), the military (Hohmann & Orlick, 2014), and medicine (Amutio et al., 2015; Anton et al., 2017; Jain et al., 2007; Wetzel et al., 2011), and even showed positive correlations with performance (Parnabas et al., 2014). Talking about long-lasting performance excellence, Orlick (2016) emphasizes that relaxation and activation are not contradictory, but that the balance of both dimensions contributes to MR.

Transferring the importance of relaxation to ERTs, it plays a crucial role because the operations are characterized by high physical and emotional demands. Relaxation techniques can thus help professionals in the emergency services to regulate their level of arousal in order to perform at their best, particularly during complex operations. Hence, the following hypotheses can be deduced:

• H5a: Relaxation affects the perceived stress in ERTs

• H5b: Relaxation affects the task performance in ERTs

• H5c: Relaxation affects the operational success in ERTs

Self-Confidence

Contrary to optimism—a person's fundamental belief to succeed—self-confidence is a situational trait which describes a person's belief in succeeding in a particular task (Feltz, 1988; Perry, 2011). Self-confidence and self-efficacy (Bandura, 1977) are often used synonymously, but self-efficacy refers to both possessing and actually using the skills needed to succeed (Bandura, 1977; Schwarzer & Jerusalem, 2002). Compared with Bandura's (1977) definition of rather situation-specific self-efficacy, George (1994) describes self-confidence as more global. The relationship between performance and self-confidence has been studied many times in the fields of sports (Gould et al., 1981; Highlen & Bennett, 1979) and education (Lane et al., 2004; Tavani & Losh, 2003). Both self-serving attribution of past performance (Kelley & Michela, 1980) and some dimensions of MR, such as positive self-talk (McDonald et al., 1995) and goal setting (Locke & Latham, 1985), can serve as sources of self-confidence. Orlick (2016) postulates that a lack of self-confidence manifests itself in mental barriers imposed by oneself or others, which inhibit performance excellence. Hence, it is not technical abilities but rather one's belief in the possibility to be successful that contributes to a higher degree of MR.

Self-confidence plays a major role in ERTs because there is no room for doubt in time-sensitive operations, requiring one to make fast decisions on saving human lives. Therefore, it is also essential that self-confidence must not lead to overestimation of one's own abilities to prevent serious consequences of errors (Rall & Langewand, 2016). Hence, the following hypotheses can be derived:

• H6a: Self-confidence affects the perceived stress in ERTs

• H6b: Self-confidence affects the task performance in ERTs

• H6c: Self-confidence affects the operational success in ERTs

Self-Talk

Self-talk refers to a mental strategy involving talking to oneself either out loud or internally in the form of keywords, short phrases, or entire sentences (Driskell et al., 1994; Hughes et al., 2011). Reframing is a coping strategy which can turn negative self-talk, which quite often follows automatically as a reaction to stressful situations, into positive self-talk by consciously focusing on positive aspects (Hughes et al., 2011). Besides the value of self-talk, there is a distinction between motivating (e.g., “Pull yourself together”) and instructional (e.g., “Focus the target”) self-talks (Gammage et al., 2001). Research has shown that there are links between self-talk and performance (Hatzigeorgiadis et al., 2011; Theodorakis et al., 2000, 2001). Furthermore, it was shown that instructional and motivating self-talk particularly improved the performance of precision tasks, whereas motivating self-talk improved the results of power tasks (Hatzigeorgiadis et al., 2004). The motivational benefit results from shifting one's focus to positive aspects and strengths even when things are supposedly bad (Lee-Gartner, 2006 cited in Orlick, 2016). Just as persuasion and concentration on one's own strengths increase self-confidence (Hatzigeorgiadis et al., 2009), making use of positive self-talk contributes to a higher degree of MR.

Accordingly, instructional self-talk can be considered to increase performance against the background of the high degree of responsibility for ethically and legally acceptable decisions ERTs are involved in (Clohessy & Ehlers, 1999; Mohr et al., 2017; Wild et al., 2018). Additionally, stress reduction and increased self-confidence to withstand the pressure to succeed because human lives are at stake can be achieved using motivational self-talk. Therefore, the following hypotheses can be derived:

• H7a: Self-talk affects the perceived stress in ERTs

• H7b: Self-talk affects the task performance in ERTs

• H7c: Self-talk affects the operational success in ERTs

Participants

A statistical power analysis was performed for sample size estimation, based on data from the meta-analysis by Driskell et al. (1994). The effect size in the meta-analysis representing 35 studies and 3,214 subjects was small to moderate (r = .25). Thus, with alpha = .05 and power = 0.95, the projected sample size needed was approximately N = 314. In total, 319 people involved in ERTs were surveyed regarding their level of MR during their operations as well as their respective task performance, success, and stress. Consequently, our proposed sample size was adequate for the main objective of this study. The specific demographic data sorted by ERT domain can be found in Table 1. As can be seen in the table, the gender distribution varied between the different ERT domains. For instance, the vast majority of emergency medical technicians and firefighters were male, whereas in the field of ICU nurses it was the other way around. There were also huge differences in age and work experience within and between the groups as can be seen in the large standard deviations and mean differences. The group of surgeons did not state their work experience in years but indicated it by their level of job position. Based on the total mean value of 11.28 years, many participants of the total sample can be regarded as highly experienced in their jobs.

TABLE 1 Demographic Data Sorted by ERT Domain

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Materials

A questionnaire was used that consisted of two parts. Part one comprised the Mental Readiness Scale (MRS; Marquardt et al., 2018), which included 53 Likert-items with a seven-point-scale (1 = totally disagree to 7 = totally agree), specifically designed for MR aspects of ERTs. The MRS encompasses seven subscales: activation (4 items), attentional control (9 items), goal setting (7 items), imagery (10 items), relaxation (8 items), self-confidence (7 items), and self-talk (8 items). Example items for each MR subscale are illustrated in the appendix.

The second part of the questionnaire contained three criterion measures: perceived stress, task performance, and success of the operation. According to Campbell et al. (1993), “performance consists of goal-relevant actions that are under the control of the individual” (p. 41). However, in the field of human performance research there is a distinction between the action under the control of the human being and the outcomes of this action. Therefore, Campbell et al. (1993) advocate for the position that task performance refers to the action itself, not the result of this action. In contrast, other researchers emphasize the outcome of these actions (Bernardin et al., 1998), which can be related to as the success of the operation. Nevertheless, performance metrics in the context of ERTs remain underdeveloped due to the inherent dynamic and complex nature of those task environments (Simpson & Hancock, 2009). As a consequence, due to the lack of objective performance measures in ERTs, task performance (2 items) and success of the operation (1 item) were assessed by the use of seven-point self-rating scales (1 = very bad to 7 = very good). Perceived stress (2 items, during task preparation and during operation) was also rated on a seven-point self-rating scale (1 = very relaxed to 7 = highly stressed) because it was not possible to use objective stress measures during the completion of ERTs.

Sampling and Procedure

We used purposive convenience sampling to recruit participants working in ERTs in Germany. The MRS, questions about demographic data, and the criterion measures (perceived stress, task performance, and operational success) were presented via paper-and-pencil questionnaire at the hospitals of the ICU nurses and the fire station of the surveyed firefighters. In the cases of the surgeons and the emergency medical technicians, the questionnaire was sent online via a web survey link. Only complete questionnaires were used for data analysis. The response rates of the single ERT domains were very different. Whereas the response rates of the paper-and-pencil questionnaires were quite high (ICU nurses: 83% = 68 of 82; firefighters: 89% = 61 of 68), those of the online survey were rather low (emergency medical technicians: 12 % = 146 of 1143; surgeons: 5% = 44 of 873).

Approximately 15 minutes were needed to complete the entire questionnaire. To ensure a full understanding of the constructs mentioned in the questionnaire, certain terms (i.e., operation, operational preparation, visualization, relaxation, self-talk, activation) were explained to the respondents at the beginning of the questionnaire.

Data Analysis

In order to test the hypotheses H1–H7, three multiple linear regression analyses were conducted. Additional requirements were mostly met for the three multiple linear regression models. That is, all residuals did not autocorrelate (Durbin-Watson values 1.88–2.05), but were not normally distributed in the regression analyses with performance and success as regressands according to Shapiro-Wilk tests (ps < .001, respectively). However, multicollinearity could be excluded (variance influence factor values 1.10 to 1.96). The results of Breusch-Pagan tests yielded overall nonsignificant models for the regression models indicating no heteroscedasticity to be violated against. Because multiple linear regression analyses are rather robust when it comes to violation of preconditions, all analyses were conducted.

Reliabilities and Descriptive Statistics

As can be seen in Table 2, the reliabilities of the MRS subscales ranged from acceptable (e.g., activation α = .67) to excellent (e.g., self-confidence α = .92). The mean values indicated a moderate (e.g., relaxation) to relatively high level (e.g., self-confidence) of MR within this sample. The three dependent measures perceived stress (M = 3.79; SD = 1.39), task performance (M = 5.77; SD = 0.75), and success of the operation (M = 5.67; SD = 1.03) indicated a moderate stress level during the ERTs and relatively high performance and success of the ERTs. In addition, there was a huge range within the correlation coefficients. While most MR subscales showed medium intercorrelations, the variables age and work experience correlated rather low with the MR dimensions and performance criteria.

TABLE 2 Descriptive Statistics and Correlations for MRS Subscales

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Hypothesis Testing (H1a–H7a): Mental Readiness and Perceived Stress

Table 3 summarizes the criterion validity of the single MR subscales for the dependent measure perceived stress. The multiple linear regression analysis reveals huge differences between the MR subscales. Specifically, activation, attentional control, relaxation, self-confidence, and self-talk significantly predicted the perceived stress level of people in ERTs. Therefore, the hypotheses H1a, H2a, and H5a–H7a were supported by the empirical evidence. Other subscales, such as goal setting and imagery, did not significantly contribute to this prediction, which resulted in the rejection of H3a and H4a. Attentional control had the strongest effect in stress reduction during ERTs. However, there is one interesting finding in this prediction: Whereas an increased use of attentional control, relaxation, and self-confidence reduces stress, it seems that an increased use of activation and self-talk increases the perceived stress level in ERTs.

TABLE 3 Regression Analysis for Predicting “Perceived Stress”

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Hypothesis Testing (H1b–H7b): Mental Readiness and Task Performance

Table 4 presents the criterion validity of the single MR subscales for task performance. Self-confidence and relaxation were the only MR subscales that predicted the task performance in ERTs. Thus, H5b and H6b were supported, whereas the other hypotheses had to be rejected. With a beta value of .58, self-confidence had the strongest effect on task performance in ERTs.

TABLE 4 Regression Analysis for Predicting “Task Performance”

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Hypothesis Testing (H1c–H7c): Mental Readiness and Success of the Operation

The criterion validity of the single MR subscales for the performance outcome criterion success of the operation is summarized in Table 5. Attentional control, goal setting, imagery, and self-confidence predicted the success of ERTs. Consequently, H2c–H4c and H6c were supported by the empirical results. Like in the task performance criterion, self-confidence had the strongest effect on the prediction.

TABLE 5 Regression Analysis for Predicting “Success of the Operation”

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Interpretation of Results

As has been shown in Tables 2–5, the results are mixed. The mean values of the MRS subscales (see Table 2) ranged between moderate (e.g., relaxation) and relatively high (e.g., self-confidence). In addition, it seems that not all MR dimensions equally contribute to stress reduction, task performance, and success of ERTs. In regards to stress reduction, relaxation techniques and attentional control can obviously lower the perceived stress level in ERTs. This result supports former studies revealing relaxation and attentional control as significant predictors for stress reduction (Marquardt et al., 2018; Orlick, 2016; Parnabas et al., 2014). Furthermore, scales such as activation and self-talk are positively correlated with stress. It is probable that psyching-up strategies as a part of the activation dimension and the use of self-talk might lead to overarousal which ultimately causes stress (Weinberg, 2010). It is very likely that the high arousing task environments in ERTs represent enough mental stimulation for those people involved (Perroni et al., 2014; Smith, 2011; Wetzel et al., 2011; Wild et al., 2018).

According to the task performance criterion, only the self-confidence and relaxation dimensions seem to be relevant. This result is partly in line with previous empirical findings from performance psychology which showed that believing in one's competence affects stress perception as well as effectiveness of task management (Zajacova et al., 2005). However, the low and nonsignificant regression coefficients of other MR dimensions such as imagery, attentional control, self-talk, and others contrasts with the several empirical (Batula et al., 2017; Marquardt et al., 2018; Orlick, 2016; Reiser et al., 2011) and meta-analytic findings (Driskell et al., 1994; Hatzigeorgiadis et al., 2011).

Finally, attentional control, goal setting, imagery, and self-confidence contributed significantly to the prediction of the performance outcome criterion success of ERTs. These results support previous findings. For instance, imagery revealed at least moderate effects (Driskell et al., 1994; Orlick, 2016; Reiser et al., 2011), and attentional control could also predict objective performance criteria (Marquardt et al., 2018). However, these empirical results are difficult to explain. How can attentional control and imagery, which contributed negatively to task performance, positively affect operational success, the outcome variable of task performance? As a consequence, these findings have to be examined thoroughly with additional measures in subsequent studies.

Strengths and Limitations

One advantage of the present study is the novelty of applying a human performance construct from sports psychology to the field of ERTs. As mentioned above, MR has been used to explain variations in peak performance of athletes but never in the field of ERTs' performance. With respect to three regression analyses, there is empirical evidence that specific MR dimensions are relevant in the context of ERTs. In addition, the reliability of most scales was good. The total sample size was also adequate.

Besides these strengths, there are also some noteworthy limitations. First, all criterion measures were only proxy measures in the ERT context. In this survey there was no opportunity to assess the real task performance, to measure the objective stress level during task completion, and to collect operational performance-critical success parameters such as saved lives, prevented medication errors, or delayed arrivals at the operational site. Furthermore, the internal consistency of the activation and goal-setting scale should be improved. Finally, the sample sizes were very different. Some subsamples can be considered as large (e.g., emergency medical technicians), whereas others can be considered as rather small (e.g., surgeons).

Practical Implications and Future Research

The present study has several implications for future human performance research and practice. Based on the revealed evidence, simulator and mental trainings can be designed. Because imagery, attentional control, and self-confidence were the best predictors for operational success, a promising research strategy might be to measure the level of these MR dimensions, and to test task performance and stress effects in simulator experiments. For instance, ERTs personnel could train situations as realistically as possible in high-fidelity firefighter or medical simulations. Besides physical fidelity, training principles that emphasize psychological fidelity will promote controlling distractions and coping with stress in dynamic and complex task environments, which in turn enhances self-confidence. For instance, Barsuk et al. (2009) have shown that residents had smaller error rates if they had previously received several simulation trainings. Those simulator trainings should additionally be accompanied by mental training exercises. In mental trainings, ERT personnel can be taught how to use mental preparation strategies in different contexts. In fact, there is evidence demonstrating positive effects of mental training as commonly used in sports and the field of medicine (Cocks et al., 2014). During mental training, they can learn how to improve the task efficiency by using visual imagery techniques such as mentally rehearsing the performance-critical procedural steps of a task sequence. Moreover, they can be taught when instructional and motivational self-talk is more appropriate and how to unfold the potential of attentional control in specific situations.

Finally, it should be taken into account that the task performance and operational success of surgeons, ICU nurses, emergency medical technicians, and firefighters depend on the entire team (Mohammadfam et al., 2015). Hence, it is important that emergency response teams ensure emergency preparedness by engaging in proactive team briefings (e.g., STICC briefing protocol, Christianson et al., 2011), effective communication pattern (e.g., closed-loop communication, Jouanne et al., 2017), and team debriefings (e.g., after-action reviews, Villado & Arthur, 2013) to maintain a shared situation awareness and MR before, during, and after task completion (Marquardt, 2019).