Is reality synonymous with perception

Gender differences in the perception of plastic as a health risk

Table of Contents

Explanation

1 Introduction

2. Basics and theoretical embedding
2.1 Basics of subjective perception
2.2 Two cognitive systems
2.3 cognitive biases (heuristics)
2.3.1 Representative heuristic
2.3.2 Availability heuristic
2.4 Perceptual deviations from reality (biases)
2.4.1 Overconfidence
2.4.2 Omission bias

3. State of research
3.1 Risk perception and underlying processes
3.2 Gender-specific risk and prevention behavior
3.3 Health risks from plastic

4. Research method

5. Field access

6. Respondents
6.1 generation
6.2 Income
6.3 Employment / occupation
6.4 Level of education
6.5 Gender

7. Selected results of the questionnaire

8. Interpretation of the results

9. Conclusion and outlook

List of figures

bibliography

Investments

Explanation

I hereby declare that I wrote the present project work independently and that I did not use any aids other than those specified.

The parts of the project work that were taken from other sources in the wording or in the sense are indicated by information on the origin.

This also applies to drawings, sketches, pictorial representations and sources from the Internet or eBooks.

I also declare that all sources used (especially those that are not freely accessible) are available and stored offline and can be made available if required.

Berlin, May 15th, 2020

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Matthias Pirog

1 Introduction

The world is full of risks. If you look at global megatrends, technical advances or social change, everyone will certainly be able to personally identify a sub-area that represents or could represent a risk for them. For example, it can be observed that risks are often perceived and assessed differently.

Let us consider a small example: “Food additives and preservatives are artificial, so it is believed that they must be dangerous. At the same time, the probability of falling ill from spoiled but “natural” foods is greatly underestimated ”(Dohle 2010).

The question would then be how a gap arises between objective facts and subjective perception of risks and whether there are even gender-specific differences in risk perception and assessment?

The present project work is intended to explicitly examine gender-specific differences in perception. The chosen object of investigation should be the topic "Plastic as a health risk".

In order to approach the topic theoretically, basic mechanisms of action of perception as well as cognitive distortions and perceptual deviations from reality are outlined. The current state of research has also been taken into account in order to build and substantiate the present work on scientific data.

The project work invokes, inter alia. based on work by Dohle (2010), the TU Cologne (2016), Müller-Peters and Gatzert (2016), Kahnemann and Tversky (1982) and analyzes by the Federal Institute for Risk Assessment (2019). On the basis of the selected theoretical principles and research results in the area of ​​risk perception, gender-specific risk and prevention behavior as well as health risks from plastic consumption, a fundamental understanding of multidimensional risk perception is to be created.

In order to test the theory in practice, a field test was initiated with the help of an online questionnaire that was developed in order to be able to depict the most meaningful social tenor possible and to achieve measurable results.

Furthermore, the questionnaire was made available to various target groups on different online channels. The attempt was made to obtain as heterogeneous a sample as possible by contacting a group of respondents that was as balanced as possible. So z. B. Environmental associations on the one hand and industry representatives on the other.

Subsequently, selected results of the survey are presented, analyzed and interpreted. Here, the research question is compared with the results of current research and checked for validity.

As a result, the knowledge gained should be presented in a structured manner, a critical evaluation should be carried out and an outlook should be given to future research fields.

2. Basics and theoretical embedding

The range of fears and associated weightings in terms of risk perception is very large and varied. For some, for example, the mobile phone is the greatest invention of the 21st century, others would rather see the devices banned from their lives today rather than tomorrow. Not only are the risks perceived differently in comparison, but one and the same risk is also perceived and assessed differently depending on the person (cf. Dohle et al. 2010, pp. 825–826).

2.1 Basics of subjective perception

How differently the subjective perception of risks drifts apart from their objective probability of occurrence is shown in the following diagram from the TU Cologne from 2016 (Fig. 1).

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Figure 1: Risk in the population: subjective vs. objective (Müller-Peters and Gatzert 2016, p. 35)

Here it becomes clear that objectively more frequent events are often subjectively underestimated as a risk by the population. For example, legal disputes, which statistically occur very frequently, are subjectively completely undervalued, whereas highly improbable and rare events such as deadly terrorist attacks are massively overestimated as a risk (see Müller-Peters and Gatzert 2016, p. 35f). The top 5 over- or undervalued risks and the factor by which the evaluation deviates from objective criteria can be seen in Figure 2.

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Figure 2: "Top-5" objective probability of occurrence and estimated frequency (Müller-Peters and Gatzert 2016, p. 36)

But how do these deviations in the perception of “reality” come about? Man is not a completely rational being. Two important representatives of (social) psychology who have taken on the investigation of this problem are Daniel Kahnemann and Amos Tversky. In their joint research, both came to the result that our actions are mostly superficially controlled and are subject to automatisms, habits and greatly simplified rules of thought and decision-making (heuristics). Simplified rules make everyday life easier and, if necessary, effectively, but from time to time lead to wrong decisions and wrong assumptions (cf. Wagner 2017, p. 108). There are also regular deviations from reality (biases) in the way we perceive our environment. Overestimation of oneself z. B. is a phenomenon in which our competencies, opportunities to influence and the rationality of our actions are massively overestimated and thus distorted. When it comes to decision-making, people continue to tend not to weight probabilities according to their actual importance, but rather to underestimate medium and high probabilities and overestimate low probabilities. This effect is called the possibility effect (see Müller-Peters and Gatzert 2016, p. 6).

2.2 Two cognitive systems

Tversky and Kahnemann derive two cognitive systems from these observations, system 1 and system 2. Müller-Peters and Gatzert refer to these two systems in their explanations "Autopilot" and "Pilot" (cf. Kahneman 2016, Chapter PART I : Zwei Systeme eBook (epub format); see Müller-Peters and Gatzert 2016, p. 7). In the following work, the terms system 1 and system 2 will be used further.

While system 1 is an energy-efficient system, which focuses on "habits, social norms and other clearly simplified decision-making patterns" (Müller-Peters and Gatzert 2016, p. 7) and hides information that is not immediately accessible, system 2 works with it significantly higher energy expenditure and significantly slower. However, due to the level of concentration, this system is less likely to lead to misjudgments. However, since the brain strives from evolution against the background of finite energy reserves to work as energy-efficiently as possible, i.e. resource-saving, we are mainly controlled by system 1 (see Müller-Peters and Gatzert 2016, p. 7).

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Figure 3: Mechanisms of action of the two cognitive systems (Müller-Peters and Gatzert 2016, p. 7)

2.3 cognitive biases (heuristics)

Some cognitive distortions are derived from the constellation of this two-part system, which make an objective assessment of risks and probabilities difficult. As an example, two heuristics are presented here in order to be able to provide basic explanations for the evaluation of the questionnaire used (see research method) in the course of this work.

2.3.1 Representative heuristic

The representative heuristic describes the phenomenon that people tend to attach a high degree of importance to highly improbable events. The system 1 is responsible here, which automatically and energy-efficiently carries out an evaluation of such events without giving the system 2 a signal to check this determination. Kahnemann and Tversky formulated this very aptly in their work "Fast thinking, slow thinking": "A sin of representativeness is the willingness to overestimate the frequency of improbable events [...]." (Kahneman 2016, chap. The sins of representativity eBook ( epub format)).

Obviously, with this cognitive bias, the question that System 2 would address is ignored: “How likely is that?”. Instead, the system 1 is operated with the question "How well can I imagine that?" B. the misjudgment that alcohol consumption is a very common cause of car accidents. Statistically, however, the proportion of alcohol driving as the cause of accidents in the overall accident rate is very low (see Müller-Peters and Gatzert 2016, p. 8).

2.3.2 Availability heuristic

The situation is similar with the availability heuristic. This is where the cognitive bias comes about, in that information that is more available to us, i.e. easier to grasp, and relates to us personally or our immediate environment, is preferred to information that is of statistical relevance, as this appears more abstract to us. Significant influencing factors include: the constant media and visual processing and repetition of individual, devastating events (e.g. natural disasters), as well as one's own experience and sharing in the personal environment.

This effect is recognizable and measurable e.g. B. in California. Shortly after an earthquake raged there, the rate of insurance contracts in the area of ​​provision against damage caused by natural disasters increases significantly. If the memory of or the feeling of being affected by such an event fades over time, the rate of taking out such insurance also gradually decreases again (Kahneman 2016, Chapter 13. Availability, Emotion and Risk eBook (epub format)). However, the statistical probability that would support such a hedging behavior is missing. Rather, the decision in this case is significantly influenced by emotions. In addition to emotionality, there are a number of other amplifiers of perception, as illustrated in the following figure.

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Figure 4: Factors influencing availability (Eller et al. 2013)

2.4 Perceptual deviations from reality (biases)

In addition to the cognitive distortions, our perception of reality is clouded by so-called biases, i.e. deviations of our perceptions from reality. The overestimation of oneself and the “distortion of omission” are particularly mentioned here.

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