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Meetbaarheid van ‘openheid voor verandering’ door middel van de geautomatiseerde methoden : een literatuurreview

Kimirilova, Julia (2018) Meetbaarheid van ‘openheid voor verandering’ door middel van de geautomatiseerde methoden : een literatuurreview.

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Abstract:Introduction. One of the factors that play a role in therapy success is 'openness to change'. So far ‘openness to change’ has been measured through questionnaires. However, this method has a number of disadvantages, among which the most important is that it provide indirect measurement that can lead to socially desirable answers. Text mining is an automated method that allows more direct measurement by examining everyday language use. Due to the popularity of e-health, this method is increasingly being applied within psychology. This led to the following research question: "Which automated methods can be used to measure 'openness to change'?" To answer this question, a literature review was carried out. Method. The search strategy consisted of a combination of key-word driven database searches in data bases Scopus, Web of Science, PsychINFO and Google Scholar with 20 key words of which the most important were ‘openness to change’, ‘openness to experience’ and ‘text mining’, and snowballing based on the references of useful articles. Research strategy was broadened after the search combination of 'openness to change' and ‘text mining’ didn’t give any results. In all cases this resulted in articles in which personality trait 'openness to experience' was measured through text mining. Openness to experience is one of the aspects of 'openness to change'. Results. The definition of 'openness to experience' appeared to vary per article, from no definition or very poor to a very extensive definition. However, in all cases it was mentioned that it was about Big Five personality trait. Moreover, different questionnaires were used to measure ‘openness to experience’ although the IPPI questionnaire dominated. Furthermore, in every study the researches tried to achieve sufficient mass of (textual) information to enable better prediction value. Finally, linguistic features, extracted from the textual content, were found to outweigh the use of non-linguistic features for the personality trait 'openness to experience'. Conclusion. Text mining makes measuring concepts such as 'openness to experience' possible by applying non-linguistic features in addition to the linguistic features. This means that non-textual data can also be measured. The use of both types of features, can make the measurement of 'openness to change' much better by means of text mining than with the questionnaires. However, 'openness to change' must be well defined, because a good and complete definition promotes reliability by making clear what should be measured by analyzing (textual) data. Still, the question remains if the non-textual data and non-linguistic features are useful in the therapeutic setting. This gives the researches a new motive for further research. Furthermore, some limitations of the study and new ideas for further research are discussed.
Item Type:Essay (Master)
Faculty:BMS: Behavioural, Management and Social Sciences
Subject:17 linguistics and theory of literature, 18 languages and literature, 54 computer science, 70 social sciences in general, 77 psychology
Programme:Psychology MSc (66604)
Link to this item:https://purl.utwente.nl/essays/76822
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