Personal informatics (PI) technologies allow unprecedented opportunities to track and analyze complex data about ourselves. However, a concern is that these technologies can make normative assumptions about user goals and ideal outcomes. Such assumptions could be especially problematic for Affective PI, as there is a risk that technologies which reflect implicit goals for users be more positive or reduce stress could ironically decrease well-being (Mauss et al., 2011). Furthermore, users could actively avoid PI data if they feel unable to meet the demands of the system (Duval & Wicklund, 1972), running counter to the view that users will engage data for beneficial insights (Kersten-van Dijk et al., 2017). We tested whether Affective PI systems that reflect goals for particular emotion outcomes (Improvement) have counterproductive effects for well-being and user engagement. These outcomes were contrasted against systems that instead reflect goals for Self-Knowledge, a top user interest (Hollis et al., 2018). Study 1 examined the effects of implicit goals in the context of an automatic stress detection and feedback system used during an exam. Participants viewed instructions that either describes the system goal as stress reduction (Improvement), stress reduction with a relaxation strategy (Self-Efficacy), accurate self-knowledge (Self-Knowledge), or saw no system goal (Control). Study 2 was a 21-day field study during which participants used a manual emotion-tracking web app that either emphasized a goal of increased positivity (Improvement), a goal of accurate self-knowledge (Self-Knowledge), or only completed pre-post surveys (Control). For each study, participants completed measures of well-being and engagement with the experimental systems. Across both studies, there were no significant condition differences in well-being. However, participants in the Self-Knowledge conditions of both studies considered themselves significantly more successful at achieving the system goals. As a result, Self-Knowledge participants were also more engaged with the stress- and emotion-tracking systems. Unlike prior work showing the ironic effects of emotional positivity goals, we show such negative impacts do not occur in this real-world context. We discuss these results with design implications for self-tracking systems and deepen the theoretical understandings of how users engage with PI.
|Commitee:||Bonett, Doug, Fox Tree, Jean E., Takayama, Leila|
|School:||University of California, Santa Cruz|
|School Location:||United States -- California|
|Source:||DAI-B 80/06(E), Dissertation Abstracts International|
|Subjects:||Cognitive psychology, Bioinformatics|
|Keywords:||Emotion, Personal informatics, Quantified self, Self-awareness, Self-knowledge, Well-being|
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