Do You Have a Minute? The Interrupted Brain

The Impact of Interruption on the Brain

Inspired by consideration of the impact on task switching and mood caused by unplanned interruptions and distractions in an open office, I decided to explore a selection of research relevant to the idea that unplanned interruptions and distractions have a negative impact on mood. This impact can be correlated to unplanned task switching and the increased cognitive load these interruptions and distractions can cause. In considering the topic, the anecdotal correlation between frequent interruption and increasing outbursts following unplanned interruption or distraction was clear. The research on the impact of distraction and interruption on the prefrontal cortex presented by Baars and Gage (2012) also supported the direction of this inquiry. I set out to understand if existing research supported the idea that the timing of unanticipated interruption or distraction had a negative impact on emotions and thus on ability to individually select tasks across the board, or if the volume of unanticipated interruptions and distractions during moments where focus was required would result in negative emotional regulation and difficulty selecting tasks and completing goals. Additionally, I wanted to understand what existing research demonstrated whether planned interruptions would have a similar negative effect, or whether only unplanned interruptions had that negative effect. My hypothesis is that frequent unplanned interruptions and distractions have a negative impact on emotional valence, cause increased cognitive load, and make tasks in progress more difficult to resume and complete.

A quick glossary of terms and theories referenced in this post

A selection of relevant research

The topic of the impact of interruption on the brain and on emotional valence is rich in research. Each facet of the research focuses on different types of interruption and the varying areas of the prefrontal cortex impacted by distraction and interruption. Research on auditory interruption (Lee et al., 2020) (Schlittmeier & Liebl, 2015) demonstrated an impact on auditory scene analysis (Baars & Gage, 2012) and lowered cognitive performance. Research on visual attention (Long & Kuhl, 2018) has shown that unplanned interruption and distraction creates a bottom-up stimulus that influences the attentional networks of the brain – the frontoparietal control network (FPCN), dorsal attention network (DAN), and ventral attention networks (VAN) specifically. Baars and Gage (2012, p. 313) call out distractions as an inhibitor to the ability to follow internally generated plans when talking about dorsolateral prefrontal syndromes. Johnson (2009) connected the dots between emotional attention set shifting and the ability to switch between tasks, which could support the idea that the negative emotion caused by unplanned interruptions makes it more difficult for subjects to self-direct which task they will focus on post interruption. Research by Sasangohar et al. (2017) on a cohort of ICU nurses studied the impact of multiple unplanned interruptions (which they termed nested interruption) on primary and secondary tasks and task resumption and the resulting increased cognitive load. Later research (Walter et al., 2020) expanded on this general idea, noting that unplanned nested interruptions had a negative impact not just on task completion and resumption, but on efficiency and safety as well, thanks to length bias and increased cognitive load. One study (Addas & Pinsonneault, 2018) focused on an area of interruption research similar to that of Sasangohar et al. – the impact of interruptions on multilevel groups (a ripple effect of interruption impact from individual to groups the individual interacts with).

The research is clear about the impact of various unplanned interruptions and distractions on the brain and on emotional valence, but what of planned interruptions? Here the research is a bit more sparse. One team (Hodgetts & Jones, 2006) found that context cues and opportunity to prepare for interruption made resuming tasks easier and creates less of a cognitive load, in line with the goal-activation model. Another study (Lee et al., 2018) compared the impact of both planned and unplanned interruptions on cognitive load to determine a framework for understanding the cost of an interruption using the NASA TLX questionnaire to inform the studies performed. Feldman and Greenway (2020) found that temporal perception across four criteria: time worthiness, timing of interruption, duration of interruption, and task expectedness supported the idea that certain planned interruptions, if well timed and meaningful, could increase positive emotional valence about the interruption and assist in task resumption after the interruption was over.  One interesting study by Parke et al. (2017) found that contingent planning for tasks that included anticipation of interruption in an office setting helps employees stay engaged even when presented with persistent interruptions (as opposed to time management planning such as to-do lists, which are more susceptible to disruption). The study by Parke et al. seems to indicate that overcoming interruption could be a learned skill. A study by Hameed et al. (2009) appears to support this as well.

While nearly every study referenced here made some mention of emotional valence in regard to interruption – usually frustration, annoyance, or anger – only one of the selected studies tried to concretely tie emotional valence and executive function together: that of Samson et al. (2022). Where many of these studies focused on some aspect of cognitive flexibility, the Samson study also included affective flexibility in the context of hot and cool cognitive processes. However, the Samson study called out what they termed “unpredictable cues” and not “interruptions” specifically.

A selection of key methodologies and findings

Two of the referenced studies had interesting and seemingly relevant findings with small, W.E.I.R.D. participant pools: Long and Kuhl’s study of the impact of bottom-up vs top-down interruptions on the brain’s attentional networks (2018) and Hameed et al.’s study of peripheral cues and their impact on reaction to interruption (2009). Long and Kuhl did a study with 32 University of Oregon students, all around 22 years old: 19 women and 13 men. They split the students into two groups. Each group had 14 participants (after some participants were excluded). These two groups participated in two experimental studies. A third group with new participants meeting the same criteria participated in a third study that was a behavioral study. The participants were monitored via fMRI while they responded to visual stimuli that involved identifying mood and gender of faces and, depending on the group, faces with and without masks, while alternating between switch and stay trials. The behavioral study with the third group mirrored the first experimental study with the addition of a behavioral questionnaire after completion. The researchers found that bottom-up attentional manipulations involving interrupted visual processing, goal relevance, and task switching have greater impact on VisN (visual cortical networks) while top-down attentional manipulations influenced FPCN, DAN, and VAN more. Hameed at al.’s research had a similar cohort of 30 students from the University of Michigan’s College of Engineering, all roughly 25 years old. In this study, participants spent 90 minutes in a space shuttle water control system simulation, the goal of which was to complete two tasks: an arithmetic task (timed focus) and an interruptive task (they were given the autonomy to decide if/when to switch attention to the interruption). The notifications for the interruptive task ranged from baseline visual notification (uninformative) to differing informative notifications (one tactile and one visual, with varying interruptive timing for each). Participants were measured during the experimental study using tactile gloves, software, and questionnaires. The study found that while both types of cues improved error detection rates both had a negative impact on focus task completion. Providing more information about the interruptive cue lowered the cost of switching tasks, however.

In two studies of auditory interruptions, one with a varied population size across several experiments and surveys conducted by Schlittmeier and Liebl (2015) and one with a small population size conducted by Lee et al. (2018), researchers sought to find a way to make interruptions more positive. Lee et al. studied 37 participants’ (all college students, 17 women and 23 men) performance on a cognitive task and a skill-based task, with the intent to measure cognitive demand, motor skill ability, and visual spatial processing to discover the cost of an interruption. The researchers also incorporated three interruption coordination modes using McFarlane’s four modes as a guide. During the within-subject experiment, participants were measured using pupil measurement, eye tracking, task performance, and self-reporting on workload, as well as completion time for tasks and task accuracy. Participants also took the NASA TLX questionnaire. The researchers found that controllability of interruptions and interruption lags had the most cognitive cost. Task similarity had lower cognitive cost, and negotiated interruptions had lower cognitive cost than other modes. They also found that primary task type had a definite impact on the cognitive cost of interruptions. Meanwhile, Schlittmeier and Liebl (2015) discuss four empirical studies seeking to understand how background speech impacts cognitive load and how interruptions are perceived. The researchers chose background speech because it is a pernicious fact of the modern-day office experience. The four studies included a subjective survey of 659 office employees regarding office acoustics, and smaller studies focusing on reduced background speech levels, partial masking, and reduced speech intelligibility and their impact on cognitive load and mood. In the n=659 participant survey, employees ranked office acoustics high in importance, ranking other employees talking, telephones ringing, and printer noises as highly disruptive (in this survey, employees talking was considered the most disruptive). The smaller studies (n1 = 20, n2 = 30, n3 = 24) focused on the impact of noise on cognitive performance and on ways to mitigate noise in an office setting to offset performance declines and cognitive load increases. In one study, highly intelligible speech signals lowered cognitive performance, while silence did not impact performance. The impact of the intelligible speech signals on cognitive load was only mitigated if the speech signals were both a. made less intelligible, and b. lowered in volume at the same time. Another study tried to mask background noise by adding more noise in the form of partially masking noises. These masking noises can be anything from white noise to the sounds of nature, played softly and continuously to cover and distract from the distracting sounds of office life. In this study the sounds of office life included ringing phones, background speech, and printers (the source signal), which was then played either on its own to the participants or covered by partially masking sounds that included broadband noise, meditation music, and baroque music. The study found that even if office noise was partially masked, it still lowered cognitive performance and created negative mood when compared to silence. Only the continuous white noise of broadband sounds reduced the negative impact of the office noise on cognitive performance and mood. The researchers (Schlittmeier & Liebl, 2015) came away with the conclusion that mitigating the drain on cognitive performance and mood would require a combination of hard scaling the office to be less conducive to sounds (such as utilizing carpet, acoustic tiles, strategically placed walls, half walls, and furniture, etc.) as well as retraining office coworkers to talk in private spaces and playing white noise to partially mask sounds.

Several of the selected studies looked at interruptions impact on the cognitive load and emotional valence of groups, in the sense of both grouped (or nested) tasks (Sasangohar et al., 2017; Walter et al., 2020) and of the impact of individual cognitive reaction to interruption on associated groups (Addas & Pinsonneault, 2018). To understand the impact of nested interruptions, Sasangohar (2017) turned to ICU nurses, as the intensive care unit (ICU) is an example of a high-stakes, high demand, interruptive work environment. In fact, the researchers state that ICU nurses can experience as many as 15 interruptions per hour depending on the unit. The researchers studied n=30 ICU nurses in a lab setting as they completed electronic order entry tasks. During the task the nurses were faced with three interruptive conditions: serial (two tasks being performed one after the other while interrupted), baseline (no secondary task while being interrupted), and nested (two tasks while being interrupted, with a secondary interruption happening during the interruption of one of those tasks). The researchers found that the nested interruptions caused longer time-to-resume the goal task, lowered accuracy of the goal task, and increased chances of costly mistakes in medication and other issues that could impact patients negatively. Taking a slightly different angle, Addas and Pinsonneault (2018) focused on how the impact of interruptions spreads beyond the cognitive load increase to an individual out to adjacent groups. They theorized that interrupting an individual had downstream impact on group work outcomes and thought that perhaps coordination theory and communication technologies could help mitigate the impact. Their paper was more a lit review of existing research done on the individual impact of incongruent interruptions and congruent interruptions from one to many, and the proposal of a methodology to mitigate the cognitive cost to the group of these interruptions (see Figure 2 below).

Feldman and Greenway (2020) took a temporal approach to solving the challenge of interruptions impact on cognitive load. To study the impact of time and context on the way interruptions increase cognitive load, create barriers to task completion, and generate negative emotions, they conducted a qualitative field study with a purposive sampled participant pool of n=35. They had the participants keep a log of interruption in diary form for one working day. Participants tracked start and end time of interruptions, who caused the interruption, what happened to interrupt them, and what task they were performing when the interruption happened, as well as how the interruptions made them feel. The researchers requested that the participants record interruptions as they happened, as well as to delve deeper into the feelings around each interruption to understand why they were having those feelings about that interruption. Completed logs were emailed to the researchers at the end of the workday. The following day the researchers conducted additional interviews of each participant, which were recorded and transcribed, designed to dig deeper into the logs. For the roughly 30% of interruptions that sparked positive feelings, the perception that an interruption was worth the participants’ time (time worthiness), had good timing (subjective judgement on whether the interruption came at a good or bad time), was of appropriate duration (how much of someone’s time the interruption was perceived to take), and was somewhat expected (whether the person being interrupted had already expected to spend time on the task or not) had the most impact on whether the interruption was seen as creating positive emotional valence. Additional factors included context, both relational and work.

Two of the studies focused more deeply on the emotional impact of interruptions: Johnson’s study on set shifting and anxiety (2009) and Samson et al.’s (2022) study of emotional regulation and executive functioning when faced with unpredictable cues (interruptions). Focusing on Samson et al.’s study of n=266 participants sought to uncover the impact of emotional regulation on cognitive function in what they termed “hot” and “cool” executive functioning processes. The participants were asked to complete a cognitive switching task with unpredictable switches that measured factors such as inhibition, attention, and cognitive emotional coping strategies. Researchers also used linear mixed modeling to understand the impact of age, gender, and switch type on the participants’ reaction times. Many of the participants were students from a university on Switzerland, all of whom spoke French as their native language. Some people were eliminated due to age or language, then the remaining participants were separated into groups: adults and teenagers. They were then asked to switch between emotional content and cognitive content in a lab setting, asked to respond as quickly as they could to the stimuli without making mistakes, and given ample time to complete each task switch. Additionally, participants were given a visual, timed Go-NoGo task involving numbers. Following the task testing, participants were given a self-report questionnaire based on the Cognitive Emotion Regulation Questionnaire (CERQ). They found that teenagers are slower to switch between cognitive and affective content than adults, and that women switch from cognitive content to affective content more slowly than they switch from affective to cognitive content.

Parke et al. (2018) takes us back to the office setting with their research on the importance of planning for interruptions as a way to mitigate their cognitive cost. They used Clear Voice Research to recruit a participant pool of n=221 office workers. they then conducted experience sampling to understand interruptions, performance, engagement, contingent planning (CP), and time management planning (TMP) each day for 10 working days across 2 working weeks. The researchers sent the participants surveys utilizing well researched questions and Likert scale ranking at 10:00 AM (to measure TMP and CP) and 3:30 PM (to measure performance, engagement, interruptions, and other control variables) each day during the study. The researchers paid the participants on an incentivized timed scale based on participation through the survey period (payment at 5-6 days, 7-9 days, and 10 complete days, respectively). There were n=187 participants who completed all 10 days, giving the researchers 1465 daily measurements. The researchers found that contingent planning is a better method to continue to complete goals and tasks in the face of interruption than time management planning (such as to-do lists), and that contingent planning also helped mitigate frustration with interruptions in the workplace.

Possible interventions suggested

Addas and Pinsonnault (Addas & Pinsonneault, 2018) suggested a model in which individuals would use technology to communicate the cost of interruptions and create solutions with the impacted group utilizing technology (CT) and providing information to address the demands of an interruption, communicating the reaction to the interruption, and coordinating the management of the interruption (see below).

Other suggested interventions included making contingent plans and to do lists instead of task focused plans and to do lists (Parke et al., 2018), utilizing office hard scaping and background noise (partial masking) to mitigate acoustic interruption (Lee et al., 2020), and training workers in how to manage their impact on others (Lee et al., 2018).

Further research ideas

I saw several potential research opportunities after researching this topic. First, it would be interesting to follow a cohort of office workers who had a hybrid work model at a large company in order to ascertain whether there was a difference in interruption cost when working at home vs interruption cost when working in an office. That study could also measure productivity levels as compared to interruption levels if done across a longer time span. Another idea would be to research how partially masking noise or, alternatively, brown noise might help people mitigate increased cognitive load and decreased executive function who have consistent internal interruptions and external. benign distractions (ADHD workers, for example). Researching the impact of rest on interruption cost would also be beneficial – much of the literature I found seemed to focus on researching during productive time and utilizing active coping mechanisms such as lists and software. However, rest is beneficial for the brain and may give workers that necessary “second wind” to regain focus. Researching the impact of play on the cognitive load increase caused by interruptions might also yield some intriguing results.

Conclusion

There were several patterns that emerged across the literature reviewed. The first being that interruption unequivocally increases cognitive load, creates strain on executive function, and causes difficulties in goal and task completion. While I was expecting to see frustration and anger mentioned often in terms of the impact of interruptions on emotional valence, it was surprising to see that some mitigation tactics can create positive emotions surrounding interruption if a number of criteria line up appropriately. One common challenge in psychological research was present across all but two of the studies: the W.E.I.R.D. participant pool. Research that focused on office workers had larger sample sizes and findings that seemed more replicable across future studies. Another trend is the impact of interruption type. Whether it was auditory, visual, or task-based interruption, sporadic interruptions for which it was hard to plan had the highest strain on cognitive load. We can reasonably conclude from this selection of studies that the cost of an interruption in both mood and brain power is high.

References

• Addas, S., & Pinsonneault, A. (2018). Theorizing the Multilevel Effects of Interruptions and the Role of Communication Technology. Journal of the Association for Information Systems, 1097–1129.
• Baars, B., & Gage, N. M. (2012). Fundamentals of Cognitive Neuroscience: A Beginner’s Guide (1st ed.). Academic Press.
• Eckart, C., Kraft, D., Rademacher, L., & Fiebach, C. J. (2022). Neural correlates of affective task switching and asymmetric affective task switching costs. Social Cognitive and Affective Neuroscience. https://doi.org/10.1093/scan/nsac054
• Feldman, E., & Greenway, D. (2020). It’s a Matter of Time: The Role of Temporal Perceptions in Emotional Experiences of Work Interruptions. Group & Organization Management, 46(1), 70–104.
• Hameed, S., Ferris, T., Jayaraman, S., & Sarter, N. (2009). Using Informative Peripheral Visual and Tactile Cues to Support Task and Interruption Management. Human Factors: The Journal of the Human Factors and Ergonomics Society, 51(2), 126–135.
• Hodgetts, H. M., & Jones, D. M. (2006). Contextual cues aid recovery from interruption: The role of associative activation. Journal of Experimental Psychology: Learning, Memory, and Cognition, 32(5), 1120–1132.
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• Johnson, D. R. (2009). Emotional attention set-shifting and its relationship to anxiety and emotion regulation. Emotion, 9(5), 681–690.
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• Long, N. M., & Kuhl, B. A. (2018). Bottom-Up and Top-Down Factors Differentially Influence Stimulus Representations Across Large-Scale Attentional Networks. The Journal of Neuroscience, 38(10), 2495–2504.
• Parke, M. R., Weinhardt, J. M., Brodsky, A., Tangirala, S., & DeVoe, S. E. (2018). When daily planning improves employee performance: The importance of planning type, engagement, and interruptions. Journal of Applied Psychology, 103(3), 300–312.
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• Samson, J. L., Rochat, L., Chanal, J., Badoud, D., Perroud, N., & Debbané, M. (2022). The Effects of Cognitive-Affective Switching With Unpredictable Cues in Adults and Adolescents and Their Relation to “Cool” Executive Functioning and Emotion Regulation. Frontiers in Psychology, 13.
• Sasangohar, F., Donmez, B., Easty, A. C., & Trbovich, P. L. (2017). Effects of Nested Interruptions on Task Resumption: A Laboratory Study With Intensive Care Nurses. Human Factors: The Journal of the Human Factors and Ergonomics Society, 59(4), 628–639.
• Schlittmeier, S. J., & Liebl, A. (2015). The effects of intelligible irrelevant background speech in offices – cognitive disturbance, annoyance, and solutions. Facilities, 33(1/2), 61–75.
• Vermeylen, L., Braem, S., & Notebaert, W. (2019). The affective twitches of task switches: Task switch cues are evaluated as negative. Cognition, 183, 124–130.
• Walter, S. R., Brown, B. M., & Dunsmuir, W. T. (2020). Detecting changes in task length due to task‐switching in the presence of repeated length‐biased sampling. Australian & New Zealand Journal of Statistics, 62(2), 133–152.
• Weigand, R., & Jacobsen, T. (2021). Interruption, work rumination, and stress as indicators of reduced working memory resources affect aesthetic experiences. Quarterly Journal of Experimental Psychology, 75(7), 1272–1288.

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