Social networking use and RescueTime

Abstract

The dramatic rise in the use of social network sites (SNS) has resulted in a number of users feeling stressed about the extent of their personal use. Previous work has established that daily retrospective estimations of SNS use and access to RescueTime not only improve accuracy of estimations but also reduce perceived stress. The present study aimed to extend this by also exploring the influence of prospective estimations on stress and perceived time management. However, the study was thwarted by incredibly low engagement with RescueTime and consequently, no improvement in estimation accuracy and no reduction in stress. This indicates substantial individual differences in engagement and a requirement for external sources of motivation for using personal informatics, beyond the tasks of the study.

Personal Informatics, Self-Insight, and Behavior Change: A Critical Review of Current Literature

“…Collins, Cox, Bird, and Cornish-Tresstail (2014) reported improved time management behaviors in their participants after using a PI efficiency tool (t = -4.38, p < .01), but only in one of their three experiments; their other outcome measures show no significant results. In a similar study, Collins, Cox, Bird, and Harrison (2014)found no effects at all. Fujinami (2010) found a significant increase in steps taken when using their system for ambient activity feedback (p < .01), but only for one of their six participants.…”

“…"; Park, Pedro, and Oliver (2015) included questions like "Did the tool help you discover your habits that you were not aware of" and "Did the findings motivate you to consider changing your browsing habits"; and Cuttone and Larsen (2014) asked participants "if they discovered something new about their own behavior." Collins, Cox, Bird, and Cornish-Tresstail (2014) used a more objective measure, investigating whether participants' estimations of their social network usage improved in response to feedback on the same (also see Collins, Cox, Bird, & Harrison, 2014). Three studies asked about participants' responses to the feedback given by the system but focused on utility rather than specifically on insights gained (e.g., Kay et al, 2012, asked participants, "What data [if any] they found useful").…”

“…Most of these studies reported issues of low engagement with the system (Collins, Cox, Bird, & Cornish-Tresstail, 2014;Collins, Cox, Bird, & Harrison, 2014;Cuttone & Larsen, 2014;Cuttone, Lehmann, & Larsen, 2013). By contrast, Kay et al (2012) reported much higher engagement, with participants spending roughly 10 min per day interacting with the system.…”

Enabling Good Work Habits in Software Developers through Reflective Goal-Setting

“…Internal, or self-awareness can be increased through self-monitoring or self-reflection, and was shown to be valuable to identify opportunities for positive behavior change [19], [55]. In the workplace, self-monitoring tools, such as RescueTime [61], have been shown to successfully increase users' awareness about the time spent on activities, work fragmentation, and productivity, but the insights are often not actionable enough to foster productive behavior changes [3], [53], [62], [63]. Contrary, and discussed in more detail in the next section, self-reflecting might allow to overcome the challenges of self-monitoring, if people reflect actively and purposefully, which results in self-generated, actionable insights that could support goal-identification and motivate behavior change [17], [18], [19].…”

“…For example, through automated monitoring, which can provide personalized insights and statistics into developers' work, and ease the recollection part of the reflection and foster goal-identification. Existing automated monitoring systems successfully increased knowledge workers' awareness about specific aspects of work, but the provided insights were often not actionable enough for users to know how and what to change, which is why the engagement with these tools usually decreased after a few days [3], [53], [62], [63]. According to Baumer et al, the problem of most automated monitoring research is the implicit assumption that just by providing access to "prepared, combined, and transformed" data, in-depth reflection can and will occur [86].…”