Kim Kristoffer Dysthe
The project is about young people with symptoms of depression: Technological and clinical tools for early intervention in general practice. Existing literature on this topic indicates that adolescents do not talk openly about their mental problems to friends, family, and healthcare workers. Instead, they seek information on the Internet. Data consists of questions written by young people on public information websites. In line with the project, my academic interest concerns methods suitable for analyzing large amounts of text data: Text mining, machine learning algorithms for statistical calculation, qualitative content analysis, and thematic analysis. In addition, I have extra training and education in cognitive behavioral therapy.
Youth health, module 6. Cognitive-behavioral therapy module 5.
Initially, I started specializing in psychiatry when offered a job in a family medicine practice until 2011: Then I took Literary Science at the University of Oslo (1-year unit), two scholarship projects (AFU) at the Department of General Medicine, HELSAM UiO: On the praxiology of family medicine in light of care theory, and the interpretation of texts in referral letters based on theories of communication. In 2019 I was offered a position in the current project, alongside working as a GP 50% (on leave 2020/21). I also work as a consultant at Bærum Hospital medical department and the Child and adolescent psychiatry ward. Currently, I am completing a specialization in family medicine.
In the project, I collaborate with SINTEF Digital (Software and Service Innovation) on the development of analysis algorithms, as well as qualitative analysis of large text data
- Brandtzæg, Petter Bae; Skjuve, Marita; Dysthe, Kim Kristoffer & Følstad, Asbjørn (2021). When the Social Becomes Non-Human: Young People’s Perception of Social Support in Chatbots, In Yoshifumi Kitamura (ed.), CHI '21: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery (ACM). ISBN 978-1-4503-8096-6. Article No.: 257. s 1 - 13 Full text in Research Archive. Show summary