When reading a novel on the bus, one’s attention may shift away from reading to thinking about things such as what to prepare for dinner or noticing the ring tone of a nearby passenger’s phone. Such shifts of attention can be either inward, toward one’s own thoughts (i.e. mind wandering) or outward, toward an external event (i.e. a distraction). In our daily lives, the environments in which we process information can vary greatly (e.g. the number of people, peripheral sights and sounds, and secondary tasks) and these variations may influence lapses of attention in different ways. The present paper is concerned with how different task settings (i.e. research laboratory versus everyday life) influence mind wandering, distraction rates, and memory performance.
When our attention is not focused on a primary task, our ability to perform that task suffers. Lapses of attention have been associated with both self-reported cognitive errors and objective sustained attention performance failures (Cheyne, Carriere, & Smilek, 2006). Performance impairments have also been observed for specific types of attention lapses, i.e. mind wandering and distraction. In a variety of tasks (e.g. sustained attention, visual search, reading, or watching lectures), higher rates of mind wandering are often associated with greater detriments to performance (e.g. slower reaction times, greater errors, poorer memory retention; Dixon & Li, 2013; Forster & Lavie, 2009; McVay & Kane, 2009; Smallwood, McSpadden, & Schooler, 2008; Varao Sousa, Carriere, & Smilek, 2013). Similarly, distractions have been reported to negatively impact performance (e.g. poorer memory retention, slower reaction times; Banbury & Berry, 1998; Forster & Lavie, 2007; Reinten, Braat-Eggen, Hornikx, Kort, & Kohlrausch, 2017).
Researchers have also investigated the impact of, and relation between, mind wandering and distraction within a single task. Stawarczyk, Majerus, Maj, Linden, and D’Argembeau (2011) report that increased rates of mind wandering and distraction during the Sustained Attention to Response Task were related to increased response variability and errors. Additional research by Unsworth and colleagues (Robison & Unsworth, 2015; Unsworth, Brewer, & Spillers, 2012; Unsworth & McMillan, 2014; Unsworth, McMillan, Brewer, & Spillers, 2012) suggests that mind wandering and distraction are separate constructs, with distractions interfering with performance “over and above that accounted for by general lapses of attention” (Unsworth & McMillan, 2014, p. 23). Collectively, this research suggests that both distractions and mind wandering influence performance (but see Olivers & Nieuwenhuis, 2005).
What remains unclear, however, is whether the effects found in laboratory settings fully capture the role of mind wandering and distractions in everyday life. While some researchers have tried to address concerns about unnatural laboratory settings by using less controlled, more naturalistic distraction stimuli (i.e. a background television program or restaurant audio track; Pool, Koolstra, & Voort, 2003; Robison & Unsworth, 2015), these distractions are still limited to scheduled experimental events from a limited stimulus set. In day-to-day life, distractions are often more unpredictable than those experienced in a laboratory experiment.
Notably, some studies have revealed important differences in patterns of inattentiveness across laboratory and everyday settings (Kane et al., 2017; Wammes & Smilek, 2017). For instance, Kane et al. (2017) measured mind wandering rates in the laboratory while participants completed a variety of executive-control paradigms (e.g. the sustained attention to response task, the attention flanker task). These results were compared to results obtained in everyday life using experience sampling methods whereby participants responded to thought-probes on a handheld device. Two key points of divergence between mind wandering in the laboratory and in life were observed. First, mind wandering rates during laboratory tasks did not correlate with mind wandering rates collected during everyday tasks, leading the authors to conclude that “any relation between laboratory and overall daily-life mind-wandering propensities is not robust” (p. 1278). Second, while measures of executive control were related to mind wandering rates in the laboratory, they were not directly related to mind wandering rates outside of the laboratory.
The divergence between life and lab is also supported by a recent study by Unsworth and McMillan (2017) in which participants completed in-lab cognitive ability tests and then, for one week, reported mind wandering and distractions that took place while studying or while in class. In contrast to laboratory studies showing that mind wandering and distraction negatively influence performance (Banbury & Berry, 1998; Dixon & Li, 2013; Forster & Lavie, 2007; Forster & Lavie, 2009; McVay & Kane, 2009; Reinten et al., 2017; Smallwood et al., 2008; Varao Sousa et al., 2013), their results suggest that everyday reports of mind wandering and distraction were not correlated with in-lab cognitive ability measures or with academic performance. However, it is worth noting that there were exceptions in Unsworth and McMillan (2017), such that some categories of mind wandering and distraction did correlate with in-lab measures (e.g. “Mind wandering due to disinterest” correlated with most in-lab cognitive tasks, while “Distraction due to hunger” did not) (see also Kane et al., 2017; Kane et al., 2007; Unsworth, Brewer, & Spillers, 2012). These results suggest that the negative consequence of attentional failures is not absolute and varies with task setting. This dovetails with the idea that the true diversity and impact of inattention in everyday environments may not have been captured by previous studies of mind wandering and distraction in the lab.
Studies of mind wandering during university lectures also show different patterns of mind wandering between lab and life settings. When students are asked to watch video recordings of lectures in the laboratory, mind wandering rates typically increase as the lecture progresses (Farley, Risko, & Kingstone, 2013; Risko, Anderson, Sarwal, Engelhardt, & Kingstone, 2012; Wammes & Smilek, 2017). In contrast, when attending a live lecture, mind wandering rates of undergraduates remain stable across the lecture (Wammes, Boucher, Seli, Cheyne, & Smilek, 2016; Wammes & Smilek, 2017).
Given recent results indicating a divergence in mind wandering rates across laboratory and real-life situations, determining why such a divergence occurs becomes an issue. One plausible reason for the divergence, which we focus on here, concerns the availability of distractions in the laboratory and in everyday life. In the laboratory, testing situations are typically controlled, with very few distractions available to co-opt attentional resources. In fact, laboratory settings are specifically designed to reduce and control distraction. In such cases, mind wandering is often the primary way (if not the only way) that inattention can be manifested. In contrast, within the natural world, opportunities for distraction seem frequent and diverse (e.g. the presence of other people, peripheral sights and sounds, media devices). In such a complex setting, inattention may be expressed in ways other than mind wandering. If the rate and impact of inattention differ between the lab and the outside world, previous lab research may be underestimating the impact that inattention has in uncontrolled environments.
To determine whether rates of inattention differ when inside and outside of the lab, we manipulated whether participants listened to an audiobook while inside the lab (controlled setting) or outside the lab (uncontrolled setting). We allowed participants to move freely outside the lab to reduce the constraints of a lab testing room and amplify the “noise” due to the perceptual richness or affordances found in everyday environments. We chose an audiobook task for two reasons: (1) mind wandering occurs frequently and reliably in this setting (Kopp & D’Mello, 2015; Varao Sousa et al., 2013); and (2) an audiobook allows one to move freely while still completing the primary task of listening. While listening, participants were prompted by an audio tone to report whether they were on task, mind wandering, or distracted. With this design we could compare rates of mind wandering and distraction in an uncontrolled everyday environment with those in a controlled lab environment. The decision to allow participants to move freely while outside the lab was in keeping with the fundamental methodology of cognitive ethology (Kingstone, Smilek, Birmingham, Cameron, & Bischof, 2005; Kingstone, Smilek, & Eastwood, 2008; Smilek, Birmingham, Cameron, Bischof, & Kingstone, 2006). Our goal was to first discover what people naturally do in an everyday environment and how that impacts cognition. Thus, participants were not instructed on how they should behave outside the lab, anticipating that choices made would reflect normative behavioral responses.
We predicted that rates of inattention would not be equivalent between life and lab environments. Specifically, we predicted participants outside the lab would report more instances of distraction, relative to mind wandering, than those inside the lab, as the former affords exposure to a greater array of dynamic stimuli. Since mind wandering is an internally driven process, we had no reason to predict that different external environments would influence the rates of mind wandering. Since Unsworth and McMillan (2014) found that distractions impaired memory test performance, and that we predicted greater distraction outside the lab, we further predicted that memory test performance should be worse when the audiobook was listened to outside the lab than inside. We also conducted an exploratory analysis to see if self-reported ratings of interest, motivation, or boredom (factors commonly correlated with mind wandering) were influenced by the task setting or were related to these attention measures.