Which model to reduce stress is concerned with the causal role played by inner dialog?

Learned Helplessness

M.E.P. Seligman, C. Peterson, in International Encyclopedia of the Social & Behavioral Sciences, 2001

Learned helplessness refers to the maladaptive passivity shown by animals and people following experience with uncontrollable events. Learned helplessness also refers to the cognitive explanation of this phenomenon. The individual learns in one situation that responses and outcomes are independent, represents this learning as an expectation of helplessness, and then generalizes this expectation to other situations in which outcomes objectively can be controlled to produce passivity. Learned helplessness has been extensively studied as an analogue of such significant human problems as depression, failure, and susceptibility to illness. An important influence on the degree of helplessness shown by people is how they explain the causes of the original uncontrollable events. Individuals who tend to explain such events with internal (‘it's me’), stable (‘it's going to last forever’), and global (‘it's going to undermine everything’) are said to have a helpless or pessimistic explanatory style. Current lines of research in learned helplessness include investigations of the biochemical substrate of the phenomenon, cross-cultural differences in its manifestation, and strategies for immunizing children against helplessness and its negative consequences.

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On the self-similarity of traffic generated by network traffic simulators

Diogo A.B. Fernandes, ... Pedro R.M. Inácio, in Modeling and Simulation of Computer Networks and Systems, 2015

5 Conclusions and future work

The simulation of network traffic plays an essential role in research and development in the networking area by allowing abstracting of underlying network complexity. It is thus crucial to find out if the simulation primitives comply with the properties exhibited by network traffic studied under real network environments. This chapter has described the self-similar nature of network traffic and discussed its presence in simulated aggregate network traffic of various computer networking scenarios.

We have provided empirical evidence of the self-similarity property to be embedded in some NS3 modeled network traffic, but not in OMNeT++. The stationarity of the bit rate per time unit is lost because of uncontrollable events during simulation runtime, producing a direct and negative impact in the self-similarity of the traffic. It was observed that the traces varied a great deal, perhaps suggesting that the simulations are highly dependent upon the simulation engine itself, and that the behavior of the modeled applications and network nodes is directly impacted by such dependence. However, it should be emphasized that the results presented throughout this chapter should be interpreted as starting points for a more thorough study of self-similarity on simulated network traffic. The VT method, for example, only covers the variance property, and so additional estimators of the Hurst parameter that explore other properties of self-similarity should be used in the future. This work does not prove that the simulators do not generate, generally speaking, self-similar traffic. However, it shows that the property should be tested whenever it is important for research work, since it may not be naturally present. Simulating this property requires fine-tuning the simulators and aggregating more sources. Additionally, goodness of fit tests for testing Gaussianity may also be employed to assess if the distribution is Gaussian.

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High-Level Architecture and Design of a Decision Engine for Marine Safety and Security1

Piper Jackson, ... Hans Wehn, in Intelligent Systems for Security Informatics, 2013

5.1 Introduction

By their very nature, some application domains are unpredictable. While we strive to develop the best technologies and practices in order to solve the problems we face, we are unable to assume that our actions will proceed without interruption. Equipment can fail and people can make mistakes. Despite the best planning, wrong decisions can be made. This is especially true in critical situations, when time is limited and the penalties for failure are severe. When we face the possibility of interference by neutral or adversarial actors, things become even more difficult. However, we are able to deal with this reality in everyday life because we are able to dynamically react to the world around us. We learn from failure and avoid problems when they become apparent. For an automated system to perform well in real-world situations, it must also be capable of doing these things.

Planning is the process of generating a series of actions that accomplish a goal. In computing, classical approaches to planning focus on theoretical properties and general algorithms. Over the last several decades, classical planning has been well studied [1]. However, a number of simplifying assumptions are made for this kind of research. Most commonly, only systems that are static, finite, deterministic, and fully observable are considered. These assumptions are appropriate only for some real-world applications, such as manufacturing, but for others they do not apply. Marine safety and security is a domain for which automated planning would be highly useful. Related operations include a mixture of routine and emergency activities, rapidly changing conditions, and complex resource requirements. Canada, with the longest coastline in the world [2], has a particular interest in innovations in this field. For automated planning to be able to perform in such a domain, it must be more flexible than a classical model allows. There are uncontrollable events and entities, imperfect knowledge and nondeterminism, i.e. actions may have unexpected results. Replanning, the dynamic generation of new plans, is a strategy that can help to address these issues.

Consider this example: A 911 call comes into a maritime services command center, initiating a search and rescue mission. A plan is put together that has the best chance of finding the capsized ship as well as any survivors within the given time window. Since we are dealing with unknowns, this plan cannot account for all eventualities. Several things can happen that could require rapid alteration of the plan. For example, new information (such as eyewitness reports) could add or remove areas of interest from the search. Another possibility is resource failure, either in the form of actual resource loss or due to situational reduction of capabilities. Bad weather is a prime cause of this, either by directly causing damage to equipment, or by interfering with movement or sensors (including vision). Finally, it is possible that a decision outlined in the plan may fail. In this case, it is a critical decision whether or not to repeat the failed action, try something else, or abort the current mission. Searching for survivors in open water during bad weather may not proceed in a textbook manner. It may be necessary to try a variety of sensing technologies or solutions, and it is possible the search attempt may become too dangerous to continue.

We propose here a comprehensive architectural model and algorithmic framework of continual planning using formal methods to represent the model at an abstract operational level, capturing the behavior of the system as a whole. Specifically, we use the Abstract State Machine (ASM) method [3] to express and delineate the responsibilities of the system components. The Decision Engine is designed to have a plug-in architecture, allowing various planning paradigms to be used within its components. For example, the set of available planning algorithms should match the needs of the domain model as represented by INFORM Lab [4], an industrial simulation platform for developing decision support systems in the marine safety and security domain (see Section 5.2.4 for more details). We also present a planning paradigm appropriate to the application domain. This design is built so that as new techniques and relevant technology are developed, they can be swapped in without difficulty. When complete, it is meant to act as a guide for future implementations of a continual planning layer.

The rest of this chapter is organized as follows: Section 5.2 discusses background knowledge and concepts related to the project; Section 5.3 presents Decision Engine design; Section 5.4 proposes a formal representation approach for the Decision Engine based on the Abstract State Machine method with some examples; Section 5.5 describes the application context in which the Decision Engine was developed; finally, Section 5.6 concludes the chapter with a discussion of future work and other possible applications of this research.

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Stress and Coping Theories

H.W. Krohne, in International Encyclopedia of the Social & Behavioral Sciences, 2001

2.2 Macroanalytic, Trait-Oriented Coping Theories

Research on the processes by which individuals cope with stressful situations has grown substantially over the past three decades (cf. Lazarus 1991, Zeidner and Endler 1996). Many trait-oriented approaches in this field have established two constructs central to an understanding of cognitive responses to stress: vigilance, that is, the orientation toward stressful aspects of an encounter, and cognitive avoidance, that is, averting attention from stress-related information (cf. Janis 1983, Krohne 1978, 1993, Roth and Cohen 1986). Approaches corresponding to these conceptions are repression–sensitization (Byrne 1964), monitoring-blunting (Miller 1980, 1987), or attention-rejection (Mullen and Suls 1982). With regard to the relationship between these two constructs, Byrne's approach specifies a unidimensional, bipolar structure, while Miller as well as Mullen and Suls leave this question open. Krohne, however, explicitly postulates an independent functioning of the dimensions vigilance and cognitive avoidance.

2.2.1 Repression–sensitization

The repression–sensitization construct (cf. Byrne 1964, Eriksen 1966) relates different forms of dispositional coping to one bipolar dimension. When confronted with a stressful encounter, persons located at one pole of this dimension (repressers) tend to deny or minimize the existence of stress, fail to verbalize feelings of distress, and avoid thinking about possible negative consequences of this encounter. Persons at the opposite pole (sensitizers) react to stress-related cues by way of enhanced information search, rumination, and obsessive worrying. The concept of repression–sensitization is theoretically founded in research on perceptual defense (Bruner and Postman 1947), an approach that combined psychodynamic ideas with the functionalistic behavior analysis of Brunswik (1947).

2.2.2 Monitoring and blunting

The conception of monitoring and blunting (Miller 1980, 1987) originated from the same basic assumptions formulated earlier by Eriksen (1966) for the repression–sensitization construct. Miller conceived both constructs as cognitive informational styles and proposed that individuals who encounter a stressful situation react with arousal according to the amount of attention they direct to the stressor. Conversely, the arousal level can be lowered, if the person succeeds in reducing the impact of aversive cues by employing avoidant cognitive strategies such as distraction, denial, or reinterpretation. However, these coping strategies, called blunting, should only be adaptive if the aversive event is uncontrollable. Examples of uncontrollable events are impending surgery or an aversive medical examination (Miller and Mangan 1983). If control is available, strategies called monitoring, i.e., seeking information about the stressor, are the more adaptive forms of coping. Although initially these strategies are associated with increased stress reactions, they enable the individual to gain control over the stressor in the long run, thus reducing the impact of the stressful situation. An example of a more controllable stressor is preparing for an academic exam.

The general relationship between a stressor's degree of controllability and the employment of monitoring or blunting strategies can be moderated by situative and personal influences. With regard to situation, the noxious stimulation may be so intense that blunting strategies, such as attentional diversion, are ineffective with respect to reducing stress-related arousal. Concerning personality, there are relatively stable individual differences in the inclination to employ blunting or monitoring coping when encountering a stressor.

2.2.3 The model of coping modes

Similar to Miller's monitoring-blunting conception, the model of coping modes (MCM) deals with individual differences in attention orientation and emotional-behavioral regulation under stressful conditions (Krohne 1993). The MCM extends the (largely descriptive) monitoring-blunting conception (as well as the repression–sensitization approach) in that it relates the dimensions vigilance and cognitive avoidance to an explicative cognitive-motivational basis. It assumes that most stressful, especially anxiety evoking, situations are characterized by two central features: the presence of aversive stimulation and a high degree of ambiguity. The experiential counterparts of these situational features are emotional arousal (as being primarily related to aversive stimulation) and uncertainty (related to ambiguity). Arousal, in turn, should stimulate the tendency to cognitively avoid (or inhibit) the further processing of cues related to the aversive encounter, whereas uncertainty activates vigilant tendencies.

These two coping processes are conceptually linked to personality by the hypothesis that the habitual preference for avoidant or vigilant coping strategies reflects individual differences in the susceptibility to emotional arousal or uncertainty. Individuals who are especially susceptible to states of stress-induced emotional arousal are supposed to habitually employ cognitive avoidance. The employment of avoidant strategies primarily aims at shielding the person from an increase in arousal (arousal-motivated coping behavior). Individuals who are especially affected by the uncertainty experienced in most stressful situations are supposed to habitually employ vigilant coping. Thus, the employment of vigilant strategies follows a plan that is aimed at minimizing the probability of unanticipated occurrence of aversive events (uncertainty-motivated coping behavior).

The MCM conceives the habitual coping tendencies of vigilance and cognitive avoidance as independent personality dimensions. That means, aggregated across a multitude of stressful encounters, the employment of vigilant strategies and of avoidant ones does not preclude each other. Thus, four coping modes can be defined. (a) Persons who score high on vigilance and low on cognitive avoidance are called sensitizers. These persons are primarily concerned with reducing uncertainty by directing their attention towards stress-relevant information. (b) Individuals with the opposite pattern are designated as repressers. These persons minimize the experience of arousal by avoiding aversive information. (c) Nondefensives have low scores on both dimensions. These persons are supposed to flexibly adapt to the demands of a stressful encounter. Instead of frequently employing vigilant or avoidant coping strategies, they prefer to act instrumentally in most situations. (d) Individuals who exhibit high scores on both dimensions are called high anxious. In employing vigilant as well as avoidant coping strategies, these persons try to reduce both the subjective uncertainty and the emotional arousal induced by stressful encounters. Because the two goals are incompatible in most situations, high-anxious persons are assumed to show fluctuating and therefore less-efficient coping behavior. Approaches to assess individual differences in vigilance and cognitive avoidance are described in Krohne et al. (2000). Empirical results related to predictions derived from the MCM are presented in Krohne (1993, 1996), and Krohne et al. (1992).

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Sports Performance, Self-regulation of

J. Beckmann, in International Encyclopedia of the Social & Behavioral Sciences, 2001

3 Self-regulation Techniques

Several self-regulation techniques have been developed which an athlete can acquire through mental training. There is no unified terminology for psychological skills training. Seiler (1992, p. 31) speaks of ‘a certain randomness of the classification, depending on the author's initial conception of what is important in sport and competition and the construction method itself.’ As a result, different mental training programs stress different elements. Most programs share a focus on the following elements: activation regulation (relaxation and energization), attention regulation (concentration), self-talk (positive thinking, thought control), imagery (visualization, mental rehearsal). In the numerous mental training programs the different techniques usually blend in with one another. For example, a lot of techniques make use of images to support self-regulation. Only the major techniques of self-regulation will briefly be described in this article.

3.1 Activation Regulation

Self-regulation in sports was often equated with relaxation, especially in the early days of sport psychological interventions. The goal was to generate a state of psychovegetative functioning, which was considered optimal for the performance of a certain task. The guiding idea behind this intervention was the, so-called, Yerkes–Dodson law of the relationship between arousal and performance. In 1908, Yerkes and Dodson found an inverted U-shaped relationship between arousal and performance in a learning experiment. In this experiment, rats learned slowest when they were highly aroused, or when their arousal was low. Their learning was fastest when arousal was at a medium level. As a consequence of this finding generations of coaches and athletes were taught that medium arousal was optimal for performance. Because the majority of athletes show a high level of arousal before a competition, relaxation was promoted as a major technique of mental preparation for a competition.

But contradictory empirical findings show that the relationship between activation and performance is more complicated than postulated in the Yerkes–Dodson law. Neiss (1988) assumed that performance impairment found in highly aroused individuals is mediated through task-irrelevant cognitions (worry) rather than through the arousal component itself. Supporting this assumption, Dienstbier (1989) reported numerous studies that show a general positive relationship between physiological arousal and performance. Beckmann and Rolstad (1997) conclude that thorough relaxation may not be the optimal preparation immediately before starting a competition. Rather, athletes should aim at increasing their precompetition activation through so-called ‘psyching up.’ But this should be combined with the self-regulation technique of thought control (avoiding negative thoughts and worries).

Although relaxation techniques may not be adequate immediately prior to or during a competition, they still play an important role in psychological skills training. They are necessary as a first step in training other self-regulation techniques. On their own, they are also an important measure for personality development (developing an even temper, the ability to ‘let go,’ supporting recovery, higher tolerance for unexpected and uncontrollable events).

Relaxation methods taught in mental training are progressive muscle relaxation (PMR) and autogenous training (AT). These rather extensive relaxation programs intend to reduce bodily activation through focusing on relaxing muscles (PRM) or autosuggestive formulas like ‘Heart beats calmly and steadily’ (AT).

A very basic technique is ‘controlled breathing.’ The breathing is conducted using the diaphragm rather than the chest. Athletes concentrate on ‘feeling the air enter the lungs and then slowly leave’ (Smith 1998, p. 42). ‘Controlled breathing’ has proven to be a good means to ‘let go,’ which means to get rid of disturbing, negative thoughts. An advantage of ‘controlled breathing’ compared to other relaxation techniques is that it does not necessarily reduce athletes' readiness for competition. Consequently, it is a relaxation technique that has its place in the preparation for competition.

3.2 Attention Control

For the majority of sport disciplines, attention is crucial for performance. Attention is threatened by various sources, especially during a competition. Through distractions athletes can lose the focus which allows them to execute their tasks effectively. Therefore, the ability to refocus in the face of distractions, to manage to concentrate on the task, is a critical self-regulatory skill.

Distractions come from a variety of sources, outside and inside athletes. The crowd, the competition conditions, a starting aircraft while an athlete tries to concentrate on her high jump, thoughts about the finishing place, or a specifically difficult and dangerous section of a downhill ski run while still gliding through an earlier section.

Nideffer (1980) made techniques of attention control popular among coaches and athletes. These techniques are used to focus or refocus attention more effectively during sport performance. One of these techniques is called ‘centering’: this is a technique used in a stressful situation to regain concentration. It involves taking a deep abdominal breath, with the individual focusing attention on the breath and then back out to a positive external cue.

Inducing positive affect (emotion control) is a frequently suggested aid in attention control. The advice is to focus on doing what will help keep the person positive and in control. The idea is that a strong positive focus protects against distractions. Usually a cognitive component is added: the athlete should develop specific, task-related goals that can capture attention; a focus that connects or reconnects to the task. This can be supported by images. Athletes can, for example, imagine being in an invisible force field. The slalom skier imagines that the slalom course is inside a tunnel of glass that keeps all possible distractions outside. Also, athletes can imagine a guiding line that carries them through their competition e.g., the downhill skier imagines a railroad track laid out along the ideal line of the downhill run.

Another, more general strategy involves relaxation training, in this case, as a form of personality development. Through relaxation training (PMR or AT), which is combined with other training routines on a regular basis, athletes can learn to ‘let go.’ They can learn not to carry mistakes with them and practice getting back on track quickly.

3.3 Self-talk and Thought Control

Another major route of self-regulatory skills for athletes became popular during the 1970s. These mental strategies are based on approaches in cognitive behavior modification which address the altering of ‘private’ cognitive processes. These techniques aim at stopping negative and destructive thoughts and promoting positive thoughts that support performance.

Gallwey (1976) has pointed out that tennis players lose their games in their heads first. When the ‘inner dialogue’ changes from a positive, confident focus to a negative one, the game is lost. Gallwey developed the so-called ‘inner game’ technique which became popular especially in tennis and golf. The inner game addresses the inner dialogue between what Gallwey (1976) calls Self 1, the analytical problem solver, and Self 2, the intuitive and emotional self. The inner dialogue can become critical, when Self 1 primarily articulates self-doubts or anxieties and thus threatens the maintenance of positive self-related control beliefs and positive self-related emotions. Strategies either have the task-related Self 2 completely occupy attentional capacity or alter the focus of Self 1 toward more positive, supportive thoughts.

The importance of having a positive inner dialogue is underlined by a study by Mahoney and Avener (1977). They found that the self-talk of US gymnasts who did not qualify for the Olympics was dominated by self-doubts and thoughts about failures. In contrast, the self-talk of those who qualified was characterized by self-confidence.

A simple technique that is often employed to stop negative thoughts is directly taken from behavior therapy: stop rules. Athletes are trained to shout ‘stop’ along with, for example, imagining a large stop sign to interrupt a negative thought sequence. But stopping the negative thoughts alone is not sufficient to get back into competition. After stopping the negative thoughts, it is important to refocus on an appropriate performance-related cue or positive thought. However, this technique involves an interruption of task performance or at least a momentary loss of concentration.

It is more efficient to prevent intrusive thoughts or negative thoughts from occurring beforehand. Beckmann (1993) used a thought-stopping technique to prevent negative thoughts, which has proven to effectively stop thoughts in numerous experiments in cognitive psychology. He had downhill skiers count numbers backwards beginning with 999 during a gliding section of a downhill run. It is impossible to think of anything else while counting the numbers. Thus, this technique prevented intrusive thoughts during that section. Because it is also quite easy to quit this task, it allows athletes to switch to task-relevant thoughts when approaching the next difficult section of the run.

3.4 Visualization

There are two applications of the visualization or mental imagery technique. One of these is used in combination with relaxation techniques to induce a positive, relaxed state of mind. The athletes visualize themselves in a favorite relaxing scene. This can be a past successful performance, that will reinstall the positive affect, the feelings of competence, or in other words, the ‘winning feeling’ that was experienced then.

The second application of visualization is to mentally rehearse performance. In this regard, visualization can be used to assist the learning of a new technique, continue practice during a period of injury, or to prepare for a competition. Neurophysiological data shows that the visualization of a physical activity is not restricted to brain processes, but actually involves small movements of ‘neuromuscular activity’ of the muscles that would be used if the activity was actually performed (MacKay 1981). The mental rehearsal of performance yields the best results, however, when visualization is used in combination with actual performance.

Eberspächer (1995) points out that ultimately athletes should be able to imagine themselves perfectly performing a task from an inner perspective, the perspective of the actor him- or herself (this is referred to as ideomotor training in a specific sense). However, it seems necessary to step by step develop and practice this inner perspective. Otherwise, an athlete may not have sufficient control over the images that come up. In visualization that is not systematically developed, unconscious fears may intrude, for example, in their ‘naive’ visualizations slalom skiers may see themselves missing a gate that they considered critical during the inspection of the run. This would, of course, not constitute a good preparation for the competition. To avoid this, Eberspächer (1995) suggests three steps during the acquisition of visualization skills:

(a)

subvocal training: write down the course of performance and then recite this course in an inner dialogue;

(b)

covered perception training: see oneself perfectly perform the activity from an outside perspective, like seeing oneself on a video (observer perspective);

(c)

ideomotor training: visualize the course of performance from an inner perspective (actor perspective).

To obtain the best results, and prevent negative thoughts and fears from intruding, it is important to execute a relaxation technique before beginning with the visualization.

3.5 Goal-setting

Numerous studies have shown that goal-setting is a self-regulation technique that works (Locke and Latham 1984). Specifically, if individuals commit themselves to specific, hard, but still realistic goals, they show better performance than when they only have a ‘do your best’ orientation. This technique supports task motivation, but also helps to focus attention on the task.

It is often important to help athletes to make their goals realistic. This means that they learn to define their goals in terms of what they can actually achieve given the state of their condition and their skills. This involves differentiating goals into short-term goals (upcoming competition), mid-term goals (standing at half-time of the season), and long-term goals (standing at the end of the season, or what one ultimately wants to achieve). In this perspective, it is helpful to introduce the image of a ladder that one intends to climb up. Take one step after another (short-term goals). You cannot expect to get to the top (long-term goal) directly from the bottom. Stay positive and confident while climbing up. You may slip down from a step from time to time (which means: don't expect to win every time), but stay oriented toward your goal, and keep climbing up steadily.

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Which of the following instruments does Fiedler's contingency theory use to determine the relevant characteristics of a leader?

In the context of this theory, leadership style is fixed and therefore can be measured using the Least-Preferred Co-Worker (LPC) Scale, a scale developed by Fiedler. The LPC scale is a questionnaire that helps the leader to understand their specific leadership style.

What is one of the most important components of leadership success and effectiveness?

Communication The art of communication is the most important element of leadership. You may have the best vision in the world, but if you can't effectively communicate it to your subordinates, it won't make much of an impact.

What two components make up credibility?

In fact, the speaker's ethos is a rhetorical strategy employed by an orator whose purpose is to "inspire trust in his audience." Credibility has two key components: trustworthiness and expertise, which both have objective and subjective components.