This thesis aims to map out the main thought processes and principles of long-distance runners. Distances stretching out up to a double marathon or even further require a substantial measure of self-motivation, which may be grounded in positive beliefs or negative past trauma of an individual. All long-distance runners are driven by a strong psychological lever which I plan to identify and describe in detail.
In this thesis, I summarize the results of some researches on this topic. Thought processes can be verbalised only to a certain extent. Today we know that our subconscious mind stores many thoughts which we cannot articulate; they rapidly come and go, slipping away before we are able to catch them. This is why we must choose questions consistently and carefully, while making sure they fulfil their purpose. These are the type of questions that I included in my questionnaire.
In a biological sense, our mentality is shaped to warn us about overexertion. It is therefore completely logical that we reach uncomfortable states and internal warnings telling us that we are doing something pointless. Top athletes, as well as good recreational athletes, are well aware of the fact that they must conquer several stages of unease in order to achieve better results.
It is human nature to engage in what we enjoy and avoid what we don't like. There are approaches that help us defeat the genetically inbuilt warnings of our psyche, hinting that our body is trying to restrain from what we are doing. Recreational athletes mostly don’t know them, since they are a part of professional sports. Pain becomes a part of recreational athletes' consciousness and most individuals don’t know how to handle it.
I used the descriptive method for analysing the researches, and conducted interviews with ten Slovene ultramarathon runners (5 men and 5 women). Based on their answers, I drew a comparison with researches done in other countries. We analysed all data in Microsoft Excel 2013 (Microsoft, Washington, USA) and in the Statistical Programme IBM SPSS 24 (SPSS Inc., Chicago, Illinois, USA). First we calculated the share of answers for all claims. We used the Mann-Whitney U Test to compare genders according to the chosen statement. We analysed all data at a 5% degree of risk and presented the results in the tables.
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