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From Quantified Self to Qualified Self: Creating a Happier User

Bardsen, K.T (2020) From Quantified Self to Qualified Self: Creating a Happier User.

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Abstract:Smart and wearable self-tracking devices have been a quintessential part of society ever since they have been brought to the mainstream market. Fitbits and smartwatches have been a fundamental part of the self-tracking culture, some more successful than others. These devices belong to what is generally known as the Quantified Self. The Quantified Self refers to the adoption of self-tracking wearables and applications that allow a user to quantify bodily functions such as step count, heart rate, sleep, caloric intake and much more. The Quantified Self has received several points of critique over the years. In this paper, the argument is made that these points of critique can be solved by applying concepts from the Qualified Self, providing the user with more context and bringing the user closer and more in alignment with their data. Specifically using “mood” as additional data is a way to bridge the gap between Quantified and Qualified self and provided context for the tracked data. I.e. how a user felt at the time. A product is proposed using these concepts. The product is a tool that measures the user’s mood, as well as factors that possibly influence mood. These factors are divided into three main categories: Social, Physical health and self care, and Productivity, and the user can attach a numerical value to these using a scale. In addition, water intake, coffee intake, alcohol intake, energy drink intake and cigarettes are tracked as well as step count and heart rate. This has the goal of showing the correlations between mood and these factors, and helping the user reflect in order to provide the tools that the user needs to improve their moods. This system was tested on seven female university students over the course of one week. The results and feedback show that dividing the list of factors into categories was effective for showing correlation between the categories and mood and increasing data granularity. However, the factors were chosen through existing state-of-the-art applications and not through literature, which leaves some doubt whether these were the most appropriate design choices. Additionally, feedback indicated that tracking mood and these factors increased personal reflection and awareness in users, allowing them to be more in control of their wellbeing.
Item Type:Essay (Bachelor)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:50 technical science in general
Programme:Creative Technology BSc (50447)
Link to this item:http://purl.utwente.nl/essays/80828
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