Teliatnykov, Ievgen (2021) Measuring correlation of cognitive functions and depression using app-based game. Bachelor's Thesis, Artificial Intelligence.
|
Text
IevgenTeliatnykov_s3547272_FinalThesis (1).pdf Download (3MB) | Preview |
|
![[img]](https://fse.studenttheses.ub.rug.nl/style/images/fileicons/text.png) |
Text
toestemming.pdf Restricted to Registered users only Download (128kB) |
Abstract
Depression is one of the most common mental illnesses. Depression refers to a prolonged state of low mood and decreased motivation. Insomnia and fatigue are common physical symptoms of depression. Interestingly, depression is even visible in smartphone behaviours. Depressed people tend to send more text messages, spend more time on a smartphone, lower time spent outdoors, and receive shorter and fewer calls than non-depressed people. Moreover, depression negatively affects executive functioning and working memory. The research aims to find out if game performance correlates with mood fluctuations, individual differences in depression and smartphone behaviour. We expect that people with more depressed moods will have worse reaction time, concentration, working memory, and, thus, worse game performance. Depressed moods will be evaluated based on self-reports and smartphone behaviour. The results have shown that more calm people tend to remember more rules. However, it was also found that more calm, fulfilled, and concentrated people were completing levels at a slower rate than those who were less calm, fulfilled and concentrated. We did not find effects of individual differences in depression and smartphone behaviour on the performance variables. The potential reason for those results is a sample bias. Around 35% of participants have left during the data collection because the study may have been too overwhelming.
| Item Type: | Thesis (Bachelor's Thesis) |
|---|---|
| Supervisor name: | Vugt, M.K. van |
| Degree programme: | Artificial Intelligence |
| Thesis type: | Bachelor's Thesis |
| Language: | English |
| Date Deposited: | 07 Sep 2021 09:21 |
| Last Modified: | 07 Sep 2021 09:21 |
| URI: | https://fse.studenttheses.ub.rug.nl/id/eprint/26057 |
Actions (login required)
 |
View Item |