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Assessing state and trait anxiety through digital phenotyping

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dc.contributor.author El-Shaarawi, Dara
dc.date.accessioned 2021-11-11T13:43:10Z
dc.date.available 2021-11-11T13:43:10Z
dc.date.issued 2021-07
dc.identifier.uri http://hdl.handle.net/10230/48955
dc.description Treball fi de màster de: Master in Cognitive Systems and Interactive Media
dc.description Directors: Klaudia Grechuta, Héctor López Carral
dc.description.abstract Mental health disorders place an immense burden on individuals and have significant personal and social impacts. This has been worsened by the effects of the COVID-19 pandemic, resulting in remote access to healthcare becoming more extensively studied and enforced. In recent years, digital phenotyping has been utilized in research to analyze and predict mental health outcomes. The aim of this project was to utilize passive mobile data to assess how anxiety impacts activity levels of individuals to help better understand their lived experiences. Potential differences between state and trait anxiety were assessed by comparing tracked and perceived activity levels. The results showed that individuals with low levels of both types of anxiety engaged in more physical activity compared to individuals with high anxiety levels. However, all participants displayed lower physical activity levels when experiencing high levels of state anxiety. Although the findings presented were very limited and lacked significance, if extended using a larger population, they could have the potential to aid in facilitating preventative interventions by detecting early signs of mental illness through evaluating possibly at-risk patients and informing the design of patient-tailored interventions.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.rights This work is licensed under a Creative Commons Attribution- NonCommercial- NoDerivs 3.0 Spain License
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.title Assessing state and trait anxiety through digital phenotyping
dc.type info:eu-repo/semantics/masterThesis
dc.subject.keyword COVID-19
dc.subject.keyword Mental well-being
dc.subject.keyword Digital phenotyping
dc.subject.keyword Anxiety
dc.subject.keyword Activity level
dc.rights.accessRights info:eu-repo/semantics/openAccess


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