Scientists have known for many years that we have attention limits that influence performance when we do more than one activity at the same time. In fact, in the late nineteenth century, a French physiologist named Jacques Loeb (1890) showed that the maximum amount of pressure that a person can exert on a hand dynamometer actually decreases when the person is engaged in mental work. Other researchers in that era also pointed out this multiple-task performance limitation (e.g., Solomons & Stein, 1896). Unfortunately, it was not until the 1950s that researchers began to try to provide a theoretical basis for this type of behavioral evidence.
The most prominent among the first theories addressing attention limitations1 was the filter theory of attention, sometimes referred to as the bottleneck theory. This theory, which evolved into many variations, proposed that a person has difficulty doing several things at one time because the human information-processing system performs each of its functions in serial order, and some of these functions can process only one piece of information at a time. This means that somewhere along the stages of information processing, the system has a bottleneck, where it filters out information not selected for further processing (see figure 9.1). Variations of this theory were based on the processing stage in which the bottleneck occurred. Some contended it existed very early, at the stage of detection of environmental information (e.g., Broadbent, 1958; Welford, 1952, 1967), whereas others argued that it occurred later, after information was perceived or after it had been processed cognitively (e.g., Norman, 1968).
A generic information-processing model on which filter theories of attention were based. The figure illustrates the several stages of information processing and the serial order in which information is processed. Filter theories varied in terms of the stage at which the filter occurred. Prior to the filter, the system could process several stimuli at the same time. In the model illustrated in this figure, the filter is located in the detection and identification stage.
This type of theoretical viewpoint remained popular for many years, until it became evident that the filter theories of attention did not adequately explain all performance situations. The most influential alternative proposed that information-processing functions could be carried out in parallel rather than serially, but attention limits were the result of the limited availability of resources needed to carry out those functions. Just as you have limited economic resources to pay for your activities, we all have limited attentional resources to do all the activities that we may attempt at one time.
Theories emphasizing attentional resource limits propose that we can perform several tasks simultaneously, as long as the resource capacity limits of the system are not exceeded. However, if these limits are exceeded, we experience difficulty performing one or more of these tasks. Theorists who adhere to this viewpoint differ in their views of where the resource limit exists. Some propose that there is one central-resource pool from which all attentional resources are allocated, whereas others propose multiple sources for resources.
Finally, more recent attention theories have moved away from the concept of a central capacity limit to one that emphasizes the selection and integration of information and activities associated with the various functional aspects of human performance, such as those depicted in figure 9.1. The primary focus of these theories has been in the area of visual selective attention, which will be discussed later in this chapter.
Central-Resource Capacity Theories
According to some attention theories, there is a central reservoir of resources for which all activities compete. Following the analogy of your economic resources, these central-resource theories compare human attention capacity to a single source from which all activities must be funded. To illustrate this view, consider a rather simplistic analogy in which the available attentional resources exist within one large circle, like the one depicted in figure 9.2. Next, consider as smaller circles the specific tasks that require these resources, such as driving a car (task A) and talking with a friend (task B). Each circle by itself fits inside the larger circle. But for a person to successfully perform both tasks simultaneously, both small circles must fit into the large circle. Problems arise when we try to fit into the large circle more small circles than will fit.
Diagram showing that two tasks (A and B) can be performed simultaneously (e.g., driving a car while talking with a passenger) if the attention demanded by the tasks does not exceed the available attention capacity. Note that the amount of available capacity and the amount of attention demanded by each task to be performed may increase or decrease, a change that would be represented in this diagram by changing the sizes of the appropriate circles.
Kahneman's attention theory. A good example of a central-resource theory is one proposed by Nobel laureate Daniel Kahneman (1973). Although this theory was originally presented many years ago, it continues to influence our present views about attention (e.g., Tombu & Jolicoeur, 2005). And although some researchers (e.g., Neumann, 1996; Wickens, 2008) have pointed out shortcomings in Kahneman's theory in terms of accounting for all aspects of attention and human performance, it continues to serve as a useful guide to direct our understanding of some basic characteristics of attention-related limits on the simultaneous performance of multiple activities.
central-resource theories of attention attention-capacity theories that propose one central source of attentional resources for which all activities requiring attention compete.
Kahneman views attention as cognitive effort, which he relates to the mental resources needed to carry out specific activities. The location of the source of these resources is central, which means the CNS; furthermore, there is a limited amount of these resources available for use at any given time. In Kahneman's model (see figure 9.3), the single source of our mental resources from which we derive cognitive effort is presented as a "central pool" of resources (i.e., available capacity) that has a flexible capacity. This means that the amount of available attention can vary depending on certain conditions related to the individual, the tasks being performed, and the situation. According to the illustration in figure 9.2, this flexible central-capacity theory states that the size of the large circle can change according to certain personal, task, and situation characteristics.
Kahneman's model of attention. [From Kahneman, D. (1973). Attention and effort, © 1973, p. 10. Reprinted by permission of the author.]
Kahneman views the available attention that a person can give to an activity or activities as a general pool of effort. The person can subdivide this pool so that he or she can allocate attention to several activities at the same time. Allocation of attentional resources is determined by characteristics of the activities and the allocation policy of the individual, which in turn is influenced by situations internal and external to the individual.
Figure 9.3 depicts the various conditions that influence the amount of available resources (i.e., attention capacity) and how a person will allocate these resources. First, notice that the central pool of available resources (i.e., available capacity) is represented as a box at the top of the model. The wavy line indicates that the capacity limit for the amount of attention available is flexible. Notice also that within this box is the word "Arousal." Kahneman included this word to indicate that the arousal level of the person significantly influences that person's available attention capacity at any given time. More specifically, a person's attention capacity will increase or decrease according to his or her arousal level. Arousal is the general state of excitability of a person, reflected in the activation levels of the person's emotional, mental, and physiological systems. If the person's arousal level is too low or too high, he or she has a smaller available attention capacity than he or she would if the arousal level were in an optimal range. This means that for a person to have available the maximum attentional resources, the person must be at an optimal arousal level.
A CLOSER LOOK An Attention-Capacity Explanation of the Arousal-Performance Relationship
A widely held view of the relationship between arousal and performance is that it takes the form of an inverted U. This means that when we graph this relationship, placing on the vertical axis the performance level ranging from poor to high, and placing on the horizontal axis the arousal level ranging from very low to very high, the plot of the relationship resembles an inverted U. This type of relationship indicates that arousal levels that are either too low or too high will result in poor performance. However, between these extremes is a range of arousal levels that should yield high performance levels. This relationship is often referred to as the Yerkes-Dodson law, which is named after two Harvard researchers who initially described this relationship in 1908 by investigating the relationship between stress and learning (Yerkes & Dodson, 1908; see also Brothen, 2012). Although the original research involved rats, many subsequent studies established its relevance to humans. It is now widely accepted as a common characteristic of human behavior.
If, as Kahneman's model indicates, arousal levels influence available attention capacity in a similar way, we can attribute some of the arousal level–performance relationship to available attention capacity. This means that arousal levels that are too low or too high lead to poor performance, because the person does not have the attentional resources needed to perform the activity. When the arousal level is optimal, sufficient attentional resources are available for the person to achieve a high level of performance.
Second, another critical factor determining whether the amount of available attention capacity is sufficient for performing the multiple tasks is the attention demands, or requirements, of the tasks to be performed. This factor is represented in Kahneman's model in figure 9.3 as the evaluation of demands on capacity. The important point here is that tasks differ in the amount of attention they demand. As a result, the person must evaluate these demands to determine if he or she can do them all simultaneously or if he or she will not be able to perform some of them.
Finally, three general rules influence how people allocate attentional resources. One rule is that we allocate attention to ensure that we can complete one activity. It is important to note here that completing one activity may not always be possible. Kahneman indicated that an activity may not be performed successfully if there is not enough capacity to meet the activity's demands or because the allocation of available attention was directed toward other activites.
A second rule is that we allocate attentional resources according to our enduring dispositions. These are the basic rules of "involuntary" attention, which concern those things that seem to naturally attract our attention (i.e., distract us). We typically will "involuntarily" direct our attention to (or be distracted by) at least two types of characteristics of events in our environment, even though we may be attending to something else at the time. An example of one of these types of characteristics is that the event is novel for the situation in which it occurs. These events can be visual or auditory. In terms of novel visual events, think about why fans at a basketball game who sit behind the basket like to stand and wave objects in the air while a player is attempting to shoot free throws. Or, consider why you become distracted while driving your car when a ball rolls onto the street in front of you. That we spontaneously and involuntary allocate our visual attention to novel events such as these is well supported by research evidence (see Cole, Gellatly, & Blurton, 2001; and Pashler & Harris, 2001, for excellent reviews of this evidence).
arousal the general state of excitability of a person, involving physiological, emotional, and mental systems. Terms such as anxiety and intensity are sometimes used synonymously in psychological contexts.
This bicycle rider, who can drink water, steer the bike, pedal the bike, maintain balance, see ahead to determine where to go and how to avoid road hazards, etc., demonstrates the simultaneous performance of multiple activities.
Unexpected noise also presents a novel event that spontaneously and involuntarily attracts our attention. For example, how many times have you directed your attention away from the person teaching your class to one of your classmates when he or she sneezes very loudly or drops a book on the floor? Consider a different type of example. Why is a professional golfer who is preparing to putt distracted by a spectator talking, when a basketball player who is preparing to shoot a free throw is not distracted by thousands of spectators yelling and screaming? The most likely reason is that the golfer does not expect to hear someone talking while preparing to putt, but for the basketball player, the noise is a common part of the game. As a result, the noise is novel in one situation but not in the other.
The second characteristic of events that will involuntarily direct our attention is the meaningfulness of the event to us personally. A classic example of this characteristic is known as the cocktail party phenomenon, which was first described in the 1950s (Cherry, 1953). Undoubtedly, you have experienced this phenomenon yourself. Suppose you are at a party in a room filled with people. You are attending to your conversation with another person. Suddenly you hear someone near you mention your name in a conversation that person is having with other people. What do you do? You probably redirect your attention away from your own conversation to the person who said your name. Why did you do this? The reason relates to the meaningfulness of your name to you. Even though you were attending to your own conversation, this meaningful event caused you to spontaneously shift your attention. In sports, it is not uncommon to hear athletes say that while they are performing, the only person they hear saying something to them is the coach. Why? In this competitive situation, the person's coach is very meaningful to the athlete.
The third rule governing our allocation of attention relates to a person's momentary intentions. This phrase means that a person allocates attention in a situation according to his or her specific intentions. Sometimes, these intentions are self-directed, which means the person has personally decided to direct attention to a certain aspect of the situation. At other times, momentary intentions result from instructions given to the person about how or where to direct his or her attentional resources. For example, if a physical therapist tells a patient to "pay close attention to where you place your foot on the stair step," the patient has the "momentary intention" to allocate his or her attention according to the therapist's instruction.
Multiple-resource theories provide an alternative to theories proposing a central-resource pool of attention resources. Multiple-resource theories contend that we have several attention mechanisms, each having limited resources. Each resource pool is specific to a component of performing skills. Using a government analogy, the resources are available in various government agencies, and competition for the resources occurs only among those activities related to the specific agencies. The most prevalent of the multiple-resource theories were proposed by Navon and Gopher (1979), Allport (1980), and Wickens (1980, 1992, 2008).
A CLOSER LOOK Attention and Cell Phone Use while Driving
A common concern throughout the world is the use of cell phones by people who are driving motor vehicles. Many countries, and some cities and states in the United States, have passed laws that prohibit cell phone use while driving. In some instances, the laws prohibit the use of both handheld and hands-free cell phones, while in other cases, laws allow hands-free cell phone use. The following information, taken from an article by Strayer and Johnston (2001), provides some basis for concern.
A study by the United States Department of Transportation indicated that as many as half of the motor vehicle accidents in the United States can be related to driver inattention and other human error.
A survey of cell phone owners reported that approximately 85 percent use their phones while driving, and 27 percent of those use the phones on half of their trips (Goodman et al., 1999; a summary of their report is available online at http://www.nhtsa.dot.gov).
A study of cell phone records of 699 people who had been involved in motor-vehicle accidents reported that 24 percent were using their cell phones within the 10 min period before the accident (Redelmeier & Tibshirani, 1997).
Although research evidence supports a relationship between cell phone use and motor vehicle accidents, the issue of cell phone use as the cause of accidents remains unsolved. However, researchers who have investigated this issue, in either car simulators or simulated driving situations in laboratories, report evidence that indicates an attention-related basis for driving accidents. In their article, Strayer and Johnson reported a series of experiments in which participants engaged in a simulated driving task in a laboratory. The results indicated these things:
Participants missed two times more simulated traffic signals when they were engaged in cell phone conversations; and, when they responded correctly to the signals (i.e., red lights), their reaction time (RT) was significantly slower than when they were not using the cell phone.
No significant differences were found between handheld and hands-free cell phone use for the number of missed traffic signals and RT (a result that is problematic for a multiple-resource theory of attention). (It is worth noting that a study by Treffner and Barrett  found critical problems with movement coordination characteristics when people were using a hands-free mobile phone while driving.)
The generation of phone conversations influenced the number of missed traffic signals and RT more than did listening to the radio or to a section of a book on audiotape.
Comparisons of conversations on cell phones and conversations with car passengers have consistently found that cell phone conversations are related to more driving errors than are passenger conversations. For example, in a comparison of driving performance while conversing on a cell phone, conversing with a passenger, and having no conversation, researchers at the University of Utah found that when drivers engaged in cell phone conversations, they increased their driving errors (Drews, Pasupathi, & Strayer, 2008). The conversation characteristics were distinctly different, which the researchers contended influenced the results. The primary difference was that passenger conversations would change as traffic situations changed, which led to a shared awareness of traffic characteristics. Cell phone conversations did not reflect this shared awareness. More recently, Strayer and colleagues (Strayer et al., 2015) have shown that using a speech-to-text system to receive and send texts and emails is even more distracting than conversing on a cell phone.
multiple-resource theories theories of attention proposing that there are several attentional resource mechanisms, each of which is related to a specific information-processing activity and is limited in how much information it can process simultaneously.
Lab 9 in the Online Learning Center Lab Manual provides an opportunity for you to experience the dual-task procedure to assess attention-capacity demands of two tasks performed simultaneously.
Wickens proposed what has become the most popular of these theories. He stated that resources for processing information are available from three different sources. These are the input and output modalities (e.g., vision, limbs, and speech system), the stages of information processing (e.g., perception, memory encoding, response output), and the codes of processing information (e.g., verbal codes, spatial codes). Our success in performing two or more tasks simultaneously depends on whether those tasks demand our attention from a common resource or from different resources. When two tasks must be performed simultaneously and share a common resource, they will be performed less well than when the two tasks compete for different resources.
For example, the multiple-resource view would explain variations in the situation involving driving a car while talking with a passenger in the following way. When there is little traffic, driving does not demand many resources from any of the three different sources. But when traffic gets heavy, resource demand increases from these two sources: input-output modalities and stages of information processing. These are the same two sources involved in providing attentional resources for carrying on a conversation with a friend. As a result, to maintain safe driving, the person must reduce the resource demand of the conversation activity.
An advantage of multiple-resource theories is their focus on the types of demands placed on various information-processing and response outcome structures, rather than on a nonspecific resource capacity. The resource-specific attention view provides a practical guide to help us determine when task demands may be too great to be performed simultaneously. For example, if one task requires a hand response and one requires a vocal response, a person should have little difficulty performing them simultaneously, because they do not demand attention from the same resource structure. Conversely, people have difficulty performing two different hand responses simultaneously because they both demand resources from the same structure. (For a more in-depth discussion of the multiple-resource view see Hancock, Oron-Gilad, & Szalma, 2007.)