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Introduction

Attention refers to the human characteristics of consciousness, awareness and cognitive effort (Anderson, & Magill, 2017). For example, consciousness and awareness denote what an individual is thinking and what they are aware of whilst performing a task, whereas cognitive effort relates to the amount concentration needed when performing a task (Anderson, & Magill, 2017).  In addition, for many years’ scientists have recognised that humans are capable of performing more than one task at the same time and can be demonstrated through daily life activities such as observing traffic whilst crossing the road or maintaining a conversation whilst driving a car (Wollesen & Voelcker-Rehage, 2013). However, limitations in attention can arise when attention capacity does not meet the task demands or when attentional resources are not shared equally (Worden, Mendes, Singh & Vallis, 2016).

Prolific attention capacity theorist Daniel Kahneman viewed attention as cognitive effort, where the allocation and availability of attention is flexible and may be improved or diminished by various factors related to the individual (Anderson & Magill, 2017). The attention demands are of particular importance to Kahneman’s theory and can be easily understood through Figure 1, where attention capacity is represented by a large flexible circle, and all activities situated within the circle are represented by smaller circles (Anderson & Magill, 2017).

A typical method of examining and assessing an individual’s attention capacity is through the dual task procedure, which commonly involves the simultaneous performance of both a motor and cognitive skill (Anderson & Magill, 2017). For example, the dual task method often requires participants to perform and maintain focus on a primary task (e.g. motor skill), whereas a secondary task (e.g. cognitive skill) is utilised to interfere and ultimately enable competition for attentional resources between the two activities (Raisbeck & Diekfuss, 2015). In a recent study, Worden, Mendes, Singh & Vallis (2016) utilised the dual task procedure to demonstrate the attention demands of walking in a challenging environment, where the aim was to emphasise the crucial role that vision has. Experimental findings indicated that participants made minimal adjustments to their movement patterns when nothing interfered with their vision, however, when presented with a visual stimulus the participants stepped over the obstacles by a higher margin and moved at a significantly slower pace (Worden et al., 2016). Therefore, the purpose of this scientific report was to practically demonstrate that humans have the attentional capacity to perform simultaneous tasks. However, it was determined that limitations and errors would arise as a result of both tasks competing for attentional resources.

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Figure 1. Example of attention capacity as a central pool for which tasks compete

Methods

Participants

Ten adults (4 females; 6 males) consented and participated in the experiment. All participants reported they were healthy and had no impairments that could hinder their ability to perform any of the tasks presented in the experiment.

Equipment

The experiment required the use of a tennis ball and a Dell Intel Pentium laptop computer equipped with a Microsoft PowerPoint presentation application. Data was collected through the use of a stop watch and figures and tables that presented the results of the experiment were created through a Microsoft Excel application.

Experimental Procedure

The experimental procedure used in this investigation was comparable to that of other dual task performance-based experiments (Worden et al., 2016). The participants were first required to stand and complete the primary motor task, which involved the use of a tennis ball that the participants threw with their preferred hand at least 30 centre metres into the air and with the same hand had to catch it. All participants were timed using a stopwatch and were instructed to complete as many catches as possible in 30 seconds whilst maintaining accuracy. Results were recorded in regards to how many catches were completed (e.g. caught with one hand).

Following the primary task, the participants were instructed to complete the secondary (e.g. interference) cognitive task, which required the participants to stand one metre from the laptop that was seated at eye level. The laptop displayed nine numbers using the PowerPoint application and the participants had to identify three of the same number in the set of nine by verbalising the number aloud (see Figure 2). The participants had to repeat this process ten times with different arrangements of numbers being displayed on each PowerPoint slide. Each PowerPoint slide remained on the screen for three seconds before moving to the next slide. Results were recorded in regards to how many groups of three of the same number the participants could correctly identify out of the ten slides.

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Figure 2. Example of the secondary cognitive task displayed on a PowerPoint slide

After the separate completion of both tasks the participants were required to complete the primary motor task and the secondary cognitive task simultaneously, where the importance of focussing primarily on the motor task was stressed to each participant. However, to avoid reporting a bias the numbers displayed on the PowerPoint slides were arranged differently compared to the first cognitive task.

Results

The results for the separate and simultaneous completion of the primary motor task and the secondary cognitive task are presented in Table 1 and Table 2, where the data demonstrates that all participants were capable of performing the primary and secondary task separately. For instance, the highest number of catches was 47 and more than 50 percent of the participants correctly identified all numbers presented in the PowerPoint presentation (see Table 1). However, results presented in Figure 3 and 4 display that compared to the separate completion of both tasks, when performing the primary and secondary task simultaneously the participants encountered difficulties, in which all made less catches and made more errors when identifying the numbers presented in the cognitive task. Specifically, Participant 1 made 46 catches when separately completing the primary task, however, was only able to complete 40 catches when performing both tasks simultaneously (see Figure 3). In addition, during the separate completion of the secondary task Participant 1 was able to correctly identify 10 of all 10 number sets presented, although, when performing the tasks simultaneously Participant 1 identified 9 of the number sets presented (see Figure 4).

Table 1

Data for the separate completion of the primary and secondary task

Table 2

Data for the simultaneous completion of the primary and secondary task

Figure 3. Number of catches for separate and simultaneous completion of the primary task

Figure 4. Number of correctly identified set of 3 for separate and simultaneous completion of the secondary task

Discussion

Central resource capacity theories describe attention as a pool of resources for which activities are situated, where according to Wollesen and Voelcker-Rehage (2013), reductions in attention capacity under dual task conditions may be due to interference by another task  or competing demands for attentional resources. The experimental findings presented in this report are therefore comparable to central capacity theories, whereby the results indicated that all participants were capable of completing the primary and secondary task simultaneously (Anderson & Magill, 2017). However, interference and limits in attention capacity caused the participants to encounter difficulties when performing both tasks concurrently. For example, the participants completed an average of 39 catches in the separate performance of the primary task, however, when performing both tasks simultaneously the participants completed an average of only 35 catches (see Table 1 & 2). In addition, there are many studies that examine attention capacity under dual task conditions which demonstrate similar experimental findings (Worden et al., 2016). One study conducted by Worden et al. (2016) utilised the dual task procedure to investigate the effects that a visual interference has when walking through a challenging environment. The experiment consisted of a visual Stroop task and a motor task, which required the participants to correctly identify the correct colour of a written word (e.g. the word green written in yellow) and walk through an obstacle course (e.g. stepping over a small hurdle). Similar to findings made in the present experiment, findings by Worden et al. (2016) indicated that participants were capable of successfully performing the tasks separately, however, all experienced difficulties when required to perform the tasks simultaneously. For instance, during the separate completion of the Stroop task and walking task all participants successfully identified 100 percent of the colours presented and did not contact any of the obstacles (Worden et al., 2016). However, when required to perform the walking and visual task simultaneously the participants cleared the obstacles by a higher margin, moved at a slower pace and identified less than 98 percent of the colours correctly (Worden et al., 2016).

Comparable findings were made by O’Shea, Morris and Iansek (2002), as they too utilised the dual task procedure to investigate the attention demands of walking in patients suffering from Parkinson’s Disease (PD). Ultimately, their study highlighted the significant connection between attention demands and movement disorders. Experimental findings indicated that compared to people without PD, people with PD had significant decreases in common gait walking characteristics when they were required to perform a motor and cognitive task simultaneously (O’Shea, et al., 2002). Specific results demonstrated reductions in walking speed whilst performing a subtraction task, in which people without PD decreased their speed only by 7.4 per cent and people with PD significantly decreased their speed by 18.5 per cent (O’Shea et al., 2002). Furthermore, similarities between the present study and O’Shea et al. (2002) are observed, where both experiments confirmed an increase in errors in the secondary cognitive task when required to perform the tasks simultaneously (see Table 2). Specifically, results by O’Shea et al. (2002) demonstrated that during the separate performance of the subtraction task the average error rate by PD participants was 0.40, however, when required to perform the subtraction and walking task simultaneously the average error rate increased to 0.76.

The results presented in the experiment demonstrate that a visual cognitive task alone may only interfere with attention capacity slightly. Therefore, although the experimental results demonstrate a decrease in cognitive and motor abilities (see Figure 3 & 4), the results did not display any significant differences. One study by Hazeltine, Ruthruff and Remington (2006) proposed that dual task conditions that involve a motor and visual-auditory task generally demonstrate a greater impact on performance and attention capacity. Hazeltine et al. (2006) investigated the effects that dual tasking has attention and reaction time (RT), where the experiment required participants respond to a variety of tones by manually pressing on the key that correctly corresponded with the pitch and by vocally categorising a set of words (e.g. tree, bug or food). Specific results demonstrated that when the participants performed the visual-auditory task separately the average RT was 600ms, however, when performing both tasks simultaneously the average RT increased to 808ms.

Conclusion

To conclude, the results from the experiment are comparable to other attention and dual task performance studies, whereby all have demonstrated that humans are more than capable of performing simultaneous tasks. Although, the studies presented show that under dual task conditions the simultaneous performance of the primary and secondary tasks was not executed as successfully (Worden et al., 2016).

References

• Anderson, D. I., & Magill, R. (2017). Motor Learning and Control: Concepts and Applications (11^th ed). New York, NY: McGraw-Hill Education.
• Diekfuss, J. A., & Raisbeck, L. D. (2015). Fine and gross motor skills: The effects on skill focused dual tasks. Human Movement Science, 43, 146-154
• Hazeltine, E., Ruthruff, E., & Remington R. W. (2006). The role of input and output modality pairings in dual-task performance: Evidence for content-dependent central inference. Cognitive Psychology, 52(1), 291-345
• Iansek, R., Morris, M. E., & O’Shea, S. (2002). Dual task interference during gait in people with Parkinson’s disease: Effects of motor versus cognitive secondary tasks. Physical Therapy, 82(9), 888-897
• Mendes, M., Singh, P., Vallis, L. A., Worden, T. A. (2016). Measuring the effects of a visual or auditory Stroop task on dual-task costs during obstacle crossing. Gait and Posture, 50, 159-163
• Voelcker-Rehage, C., & Wollesen, B. (2013). Training effects on motor-cognitive performance in older adults. European Group for Research into Elderly and Physical Activity, 11, 5-24