Brief articleChallenge and error: Critical events and attention-related errors
Highlights
► We examine human reactivity to task challenges and errors. ► Challenge and error reactivity generates a cycle of attention lapses ↔ task errors. ► Results challenge generality of current conflict monitoring and control models. ► Our bidirectional model provides framework to understand how “errors beget errors”.
Introduction
The study of reactivity to errors has had a short but active history. One common finding reported is that of post-error slowing and enhanced performance (Laming, 1968, Laming, 1979, Rabbitt, 1966, Rabbitt, 1967). Such findings have been subject to considerable and conflicting theoretical speculation (Botvinick et al., 2001, Castellar et al., 2010, Dudschig and Jentzsch, 2009, Jentzsch and Dudschig, 2009, Notebaert et al., 2009, Ridderinkhof, 2002). An influential interpretation of post-error slowing is that it reflects a conflict monitoring process that leads to a more cautious response strategy (e.g., Botvinick et al., 2001). Although response slowing, increased caution, and renewed attention to task following errors and even successfully-met task challenges clearly occurs in some contexts, to conclude that such a response style is universal and/or inherently functional, flies in the face of real-world evidence. Such evidence suggests that perceived errors frequently lead to further errors when pilots, surgeons, drivers, or industrial personnel become distracted by initial errors that rapidly become compounded as attention is diverted from ongoing task demands (Reason, 1990, Reason and Mycielska, 1982, Vincente, 2003, West et al., 2006).
Results more compatible with these particular real-world findings have recently been noted using the Sustained Attention to Response Task (SART), an increasingly widely used laboratory test of attention lapses (Robertson, Manly, Andrade, Baddeley, & Yiend, 1997). The SART requires continuous responding (key-pressing) to each of a continuous random series of single digits (1–9) except for a rare NOGO digit (3). Attention lapses are assessed by the number of commission errors on these relatively rare NOGO trials, and by speeded response time prior to NOGO errors (Cheyne et al., 2009, Robertson and Garavan, 2004, Robertson et al., 1997). In contrast to much of the literature on post-error slowing, and consistent with the error-begets-error phenomenon, in a recent study we (Cheyne et al., 2009, Cheyne et al., 2009) observed that errors on the SART were followed by increased rates of error, increased response anticipations (extremely short reaction times, <100 ms), and increased omissions (failure of timely responding within task parameters). Moreover, although we also observed a brief post-error return to baseline (i.e., slowing of response speed relative to pre-error speeding), this was immediately followed by speeding. In general, detailed analysis of these multiple consequences of NOGO trials was consistent with the interpretation that the primary outcomes of task challenges (NOGO trials) were disrupted and disorganized responding, rather than increased caution and task focus. These results were framed in a bidirectional error ↔ attention-lapse model, which stipulates that attention lapses lead to errors on NOGO trials, and that these errors can in turn lead to further attention lapses (Cheyne et al., 2009, Cheyne et al., 2009). Critically, this model stands in contrast to the common understanding of post-error changes in performance, which are thought to reflect a more cautious strategic response strategy.
In the present paper we focus on the bidirectional error ↔ attention-lapse model in which errors are hypothesized to cause attention lapses, and vice versa. In particular, we propose a challenge-induced entry to this recurrent cycle, whereby task challenges in general lead to attention lapses, and these lapses sustain the bidirectional relationship with errors. By “challenge” we mean exposure to an event or situation that engages or alters adaptive physiological or psychological processes. Task challenge consequences can induce lapses that in turn lead to errors that are themselves a particularly potent consequence leading to further attention lapses. Thus even successful performance following challenge can set off the error ↔ attention-lapse cycle when it leads to offline rumination about performance.
Internal processing of one’s task performance is a form of task-relevant rumination (McVay and Kane, 2010, Watkins, 2010) or task-relevant mind wandering (Cheyne et al., 2009, Cheyne et al., 2009). Mind wandering refers to periodic and apparently spontaneous attention shifts (Smallwood & Schooler, 2006). Mind wandering, so defined, is not limited to daydreaming but includes all explicit (conscious) cognitive activity not focused on immediate occurrent task demands. It may therefore include attentional focus on non-immediately present or relevant aspects of a task, such as overall evaluation of past performance and anticipated future task demands. Challenge-induced assessments and evaluations of successes and failures on preceding trials will sometimes persist until, and hence potentially have an impact on responsiveness to, the next trial. Importantly, we suggest that both successes and failures on previous task challenges will lead to attention lapses, but that failures to meet challenges might have a more profound impact on attention lapses than successes. Although rumination is typically associated with self-rather than task-focused, cognitions, in the absence of dysphoria rumination has been reported to be associated with high levels of task focus (Smallwood et al., 2002). Task relevant rumination is a form of task appraisal functioning as a form of task-related interference (cf. Smallwood, O’Connor, & Heim, 2004) suggested by findings that both task relevant and task irrelevant rumination are associated with SART errors (e.g., Smallwood, Fitzgerald, Miles, & Philips, 2009).
One prediction following from the error ↔ attention-lapse hypothesis is that performance on trials immediately following a task challenge will be adversely affected, and that this effect will vary as a function of the temporal distance from that challenge. Under the assumption that making an error is more salient, and requires additional processing (e.g. Jentzsch & Dudschig, 2009) compared to a correct withhold on the SART, the impact of NOGO error trials should be stronger and/or more persistent than that of NOGO trials with successful withholds, though both types of NOGO trials will adversely affect performance on subsequent trials. In a previous report we incidentally observed a positive association between error likelihood and the number of GO trials intervening between NOGO trials (Cheyne et al., 2009, Cheyne et al., 2009). Though interpretation was complicated because frequency of interval length was not controlled in that study, the higher rate of errors following more closely previous NOGO trials is consistent with task-induced attention lapses.
The present study was designed to evaluate in some detail the effects of temporal distance (measured by number of intervening trials) between successive challenge (NOGO) trials on commission errors and response times in order to assess the presence, magnitude, and persistence of the costs of challenge events and to compare this with the effects of trial position across the entire experiment (time-on-task). Our experimental design also allowed us to consider various existing interpretations of performance in the SART task, which we address in the results and in the discussion that follows.
Section snippets
Participants
Participants were randomly selected from a diverse international group of prior respondents to a WWW survey on sleep paralysis, all of whom had previously agreed to be contacted for future research. Of 3000 potential participants contacted for the study, the current sample included 339 participants who completed the SART. The present sample included 229 females and 92 males, and 18 non-specified, with a mean age of 30.06 (SD = 8.59; females M = 30.34, males M = 29.38, t (319) = .90, p = .368). An
Results
The overall mean proportion correct was .51 (SD = .23. The overall mean RT was 372.02 ms (SD = 81.00 ms). The Pearson product-moment correlation between performance and RT was r = .61, p < .001.
Discussion
The results revealed several significant effects of time since last NOGO challenge (interval length) on subsequent NOGO performance and GO response times. NOGO challenge trials were followed by decreased accuracy of performance on NOGO trials and speeded response time on GO trials. Both errors and response times recovered more rapidly following correct trials relative to error trials. Response time recovered after one intervening GO trial following a correct NOGO trial, but required 4–5 trials
Concluding remarks
In the present task, challenge trials lead to pervasive immediate negative effects on ongoing performance, lasting 6–7 s, as well as longer term interference with strategic adjustment of response times. Attention lapses, the turning of attention away from continuous monitoring of ongoing tasks, are potentially a pervasive consequence of meeting life’s everyday moment-to-moment challenges – and of succeeding or failing to meet of those challenges. Such challenges are common during everyday
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