Individual differences in lapses of attention: A latent variable analysis.

Abstract

Individual differences in lapses of attention were examined in the present study. Participants performed various attention control, working memory, and reaction time (RT) tasks to assess lapses of attention. Task-unrelated thoughts, task-specific motivation, alertness, and trait factors were also assessed. Behavioral indicators of lapses of attention correlated and loaded on the same general lapse of attention factor. The lapse of attention factor correlated with, but was distinct from, attention control and task-unrelated thoughts factors. The lapses of attention factor further related to working memory capacity, speed of processing, motivation, alertness, boredom proneness, and self-reports of everyday cognitive failures. Structural equation modeling suggested that attention control, task-unrelated thoughts, variance shared across task unrelated thoughts, motivation, and alertness, and boredom proneness all accounted for unique variance in lapses of attention. These results provide important evidence for the general tendency to experience lapses of attention in a variety of tasks and situations and further suggest that multiple factors contribute to variation in lapses of attention.

A Nomothetic Span Approach to assessing the Construct Validity of Sustained Attention Measures

“…In doing so, our argument will be that a combination of objective and subjective indicators will provide the most valid assessment of sustained attention ability and its individual-differences variation. We build this argument on the precedent that in some traditional sustained attention tasks, different performance indicators might reflect different types or degrees of sustained attention failures (Cheyne et al, 2009;Unsworth et al, 2021). For example, Cheyne et al (2009) found that anticipatory responses (i.e., responses < 100 ms), intraindividual RT variability, and omissions (target misses), all predicted unique variance in no-go accuracy in a go/no-go sustained attention task.…”

“…Accuracy-based measures from some tasks may also reflect lapses in sustained attention, at least in part. For example, in the Sustained Attention to Response Task (SART), errors of omission (i.e., not responding to a "go" target trial) and errors of commission (i.e., erroneously responding to a non-target "no-go" trial) might reflect even greater task disengagement than is captured by variable responding (Cheyne et al, 2009;Unsworth et al, 2021). That is, errors of omission might reflect a complete disengagement from the task whereas errors of commission might reflect being captured enough by monotonous responding that individuals keep making repetitive responses when they are not supposed to.…”

“…That is, errors of omission might reflect a complete disengagement from the task whereas errors of commission might reflect being captured enough by monotonous responding that individuals keep making repetitive responses when they are not supposed to. Likewise, during continuous tracking tasks, in which subjects attempt to closely follow an object onscreen with a stylus or cursor, subjects may occasionally exhibit "flat spots," or brief instances where they fail to respond to the stimuli (Unsworth et al, 2021; see also Peiris et al, 2006). 3…”

Abrupt vs. gradual visual onsets in go/no-go sustained attention tasks

“…GRADUAL ONSETS 20 those used by Jun and Lee (2021) should be combined with simultaneous measurement of other individual differences, developmental differences, and neural/psychophysiological recordings. For example, it has been demonstrated that both RT CV and no-go error rates from the SART can be used as measures of attention control in individual differences investigations (Cheyne et al, 2006;Kane et al, 2016;McVay & Kane, 2009, 2012Unsworth & McMillan, 2014;Unsworth, Robison, & Miller, 2021), and it has been demonstrated that individual differences in performance in the gradCPT can be correlated with neural measures of whole-brain functional connectivity (Rosenberg et al, 2016).…”

A "Goldilocks zone" for mind wandering reports? A secondary analysis of how few thought probes are enough for reliable and valid measurement

“…In the laboratory, the thought-probe technique has been successfully implemented in a variety of tasks, including attention-control and working memory tasks (e.g., McVay & Kane, 2009Robison et al, 2020;Unsworth & Robison, 2016), passage reading (e.g., Schooler et al, 2004;Smallwood et al, 2008;Unsworth & McMillan, 2013), simulated driving (e.g., Baldwin et al, 2017;Zhang & Kumada, 2018), and video-lecture viewing (e.g., Hollis & Was, 2016;Risko et al, 2012;Szpunar et al, 2013). Probed TUT-report rates appear to be valid individual-differences measures, as they are reliable across different tasks and occasions (e.g., Kane et al, 2016;Unsworth et al, 2020) and they correlate with other measures argued to reflect mind wandering and attentional lapses, such as RT variability (Bastian & Sackur, 2013;McVay & Kane, 2012;Seli et al, 2013b;Unsworth et al, 2010), pupil dilation and eye movements (Reichle et al, 2010;Zhang et al 2020), and retrospective self-reports of mind wandering propensity (Carriere et al, 2013;Mrazek et al 2013;Seli et al, 2016a. Variation in TUT rate is also predicted by measures of theoretically relevant constructs like working memory capacity (WMC) and attention-control ability (McVay & Kane, 2012;Kane et al, 2016;Rummel & Boywitt, "Goldilocks Zone" for Thought Probes 4 2014; Robison & Unsworth, 2018), Attention-Deficit/Hyperactivity Disorder symptoms (Franklin et al, 2017;Seli et al, 2015b;Meier, 2021), and motivation for and interest in the ongoing activity (Brosowsky et al, 2020;Robison ...…”