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Doing and feeling: relationships between moods, productivity and task-switching
File | Description | Size | Format | |
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IEEE_TAC___Doing_and_Feeling-2.pdf | Accepted version | 507.15 kB | Adobe PDF | View/Open |
Title: | Doing and feeling: relationships between moods, productivity and task-switching |
Authors: | Alibasa, MJ Purwanto, RW Yacef, K Glozier, N Calvo, RA |
Item Type: | Journal Article |
Abstract: | Digital technology influences behaviours, moods and wellbeing. The relationships are complex, but users are increasingly interested in finding how to balance a digital life with psychological wellbeing. We present an approach for investigating the relationship between lifestyle aspects and digital technology usage patterns that combines MindGauge, a mobile app enabling users collect and analyse their moods and behaviours, with a productivity tool (RescueTime). We then report a 16-month study in which we collected computer and smartphone usage and self-reports from 72 participants. We present methods for analysing the relationship between productivity, task-switching, mood and lifestyle, and more specifically how digital technology usage associates with productivity and task-switching. Our study also investigates how lifestyle aspects (sleep quality, physical activity, workload, social interaction and alcoholic drink consumption) relate to mood, task-switching and productivity. Results show that more frequent task-switching is associated with negative moods. A few lifestyle aspects, such as sleep quality and physical activity, had a significant relationship with positive moods. We also contribute a mood detection model that utilise both digital footprints and lifestyle contexts, yielding an accuracy of 87%. The study provides evidence that such methods can be used to understand the impact of technology on wellbeing. |
Issue Date: | Jul-2022 |
Date of Acceptance: | 3-Oct-2020 |
URI: | http://hdl.handle.net/10044/1/83887 |
DOI: | 10.1109/taffc.2020.3029440 |
ISSN: | 1949-3045 |
Publisher: | Institute of Electrical and Electronics Engineers |
Start Page: | 1140 |
End Page: | 1154 |
Journal / Book Title: | IEEE Transactions on Affective Computing |
Volume: | 13 |
Issue: | 3 |
Copyright Statement: | © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Keywords: | Science & Technology Technology Computer Science, Artificial Intelligence Computer Science, Cybernetics Computer Science Mood Task analysis Productivity Tools Stress Switches Digital behaviour mood detection computer logs mood and lifestyle productivity task-switching HEALTH SLEEP WORK 0801 Artificial Intelligence and Image Processing 0806 Information Systems 1702 Cognitive Sciences |
Publication Status: | Published |
Online Publication Date: | 2020-10-07 |
Appears in Collections: | Dyson School of Design Engineering Faculty of Engineering |